ܨܘܪܬܐ ܕܡܐܢ̈ܐ: ܝܕ̈ܥܬܐ ܕܒܪܢܫܘܬܐ ܕܝܓܝܛܠܝ̈ܬܐ ܘܝܕ̈ܥܬܐ ܕܟܢܫܐ ܒܚܘܫܒܢܐ
99 ܡܐܢ̈ܐ ܓܘ ܥܣܪܐ ܓܢ̈ܣܐ – ܡܘܕܝ ܟܥܒܕ ܟܠ ܚܕ، ܟܡܐ ܟܥܠܐ، ܐܝܟܐ ܝܢܐ ܝܗܝ̈ܒܬܐ ܕܝܘܟܘܢ، ܘܡܘܕܝ ܟܦܠܚ ܒܥܒܪܝܐ. ܡܢܬܐ ܐ – ܬܘܩܢܐ ܕܒܘܨܝܐ.
ܡܐ ܐܝܬ ܓܘ ܐܗܐ ܦܐܬܐ، ܘܕܟܝ ܟܩܪܚ ܠܘ̈ܚܐ
ܬܪܝܢ ܚܩ̈ܠܐ ܕܒܘܨܝܐ ܪܒܝܠܗܘܢ ܓܘ ܥܣܪܝܢ ܫܢ̈ܐ ܐܚܪܝ̈ܐ ܚܕܪ ܗܝ̇ ܥܒܕܐ – ܕܡ̈ܠܐ، ܐܣܘܪ̈ܐ، ܕܘܟ̈ܝܬܐ ܘܥܘܒ̈ܕܐ ܐܝܬܠܗܘܢ ܐܕܝܘܡ ܒܐܣܟܝܡܐ ܕܝܓܝܛܠܝܐ ܘܡܨܝܚ ܕܡܬܚܫܒܝ. ܝܕ̈ܥܬܐ ܕܒܪܢܫܘܬܐ ܕܝܓܝܛܠܝ̈ܬܐ (digital humanities, DH) ܐܬܝܠܗܘܢ ܡܢ ܦܝܠܘܠܘܓܝܐ، ܡܢ ܬܫܥܝܬܐ ܘܡܢ ܒܘܨܝܐ ܕܣܦܪܘܬܐ: ܫܘܐܠܐ ܕܝܠܗܘܢ ܝܠܗ ܡܘܕܝ ܡܨܝܚ ܕܝܕܥܚ ܥܠ ܡ̈ܠܐ، ܥܠ ܒܝܬ ܟܬܒ̈ܐ ܝܢ ܥܠ ܙܒܢܐ ܐܝܡܢ ܕܩܪܝܚ ܠܗܘܢ ܒܥܘܕܪܢܐ ܕܚܘܫܒܢܐ (Schreibman, Siemens & Unsworth, 2016). ܝܕ̈ܥܬܐ ܕܟܢܫܐ ܒܚܘܫܒܢܐ (computational social science, CSS) ܐܬܝܠܗܘܢ ܡܢ ܣܘܣܝܘܠܘܓܝܐ، ܡܢ ܝܕܥܬܐ ܕܡܕܝܢܬܐ ܘܡܢ ܝܕܥܬܐ ܕܢܦܫܐ: ܫܘܐܠܐ ܕܝܠܗܘܢ ܝܠܗ ܡܘܕܝ ܡܨܝܚ ܕܝܕܥܚ ܥܠ ܟܢܫܐ ܡܢ ܥܩ̈ܒܬܐ ܕܝܓܝܛܠܝ̈ܐ ܕܟܫܒܩ (Lazer et al., 2009, 2020; Edelmann et al., 2020). ܡܐܢ̈ܐ ܪܘܒܐ ܕܝܠܗܘܢ ܡܫܘܬܦ̈ܐ ܝܢܐ، ܘܐܗܐ ܨܘܪܬܐ ܟܡܚܘܝܐ ܠܗܘܢ ܐܟܚܕܐ – ܠܦܘܬ ܡܐ ܕܟܥܒܕܝ، ܠܐ ܠܦܘܬ ܚܩܠܐ ܕܒܕܝܠܗ ܠܗܘܢ.
ܬܚܘ̈ܡܐ ܕܚܩܠܐ ܒܢܦܫܗ ܣܓܝ̈ܐܐ ܝܢܐ، ܘ-Carter (2013, p. ix-xi) ܟܒܚܪ ܠܗܘܢ ܒܫܪܪܐ: "ܨܠܝܒܘܬܐ ܒܝܢܝ ܝܕ̈ܥܬܐ ܕܒܪܢܫܘܬܐ ܘܐܘܡܢܘܝ̈ܬܐ ܕܝܕܥܬܐ" (Svensson, 2010, as cited in Carter)، "ܙܩܘܪܬܐ ܕܚܩ̈ܠܐ" ܕܓܘܗ̇ ܟܫܐܠܝ ܫܘܐ̈ܠܐ ܡܫܠܡܢ̈ܝܐ ܕܝܕ̈ܥܬܐ ܕܒܪܢܫܘܬܐ ܥܠ ܐܘܡܢܘܝ̈ܬܐ ܘܠܗܦܘܟܐ (Fitzpatrick, 2010, as cited in Carter)، ܘܬܪܝܢ "ܓܠ̈ܠܐ" – ܟܡܝܝܐ-ܕ-corpus ܘܒܬܪܗ ܦܘܫܩܝܐ-ܢܣܝܘܢܝܐ (Schnapp & Presner, 2009, as cited in Carter). ܫܘܠܡܐ ܥܒܕܢܝܐ ܕܝܠܗ ܡܘܬܪܢܐ ܝܠܗ ܩܐ ܐܗܐ ܨܘܪܬܐ: ܠܐ ܣܢܝܩ ܝܠܗ ܕܦܠܛܐ ܠܪܡܙܐ ܩܐ ܡܦܠܚܢܘܬܐ ܕܝܠܗ، ܘܐܢܝ ܕܟܦܠܚܝ ܐܕܝܘܡ ܓܘ ܚܩܠܐ ܟܚܫܝ ܡܢ "ܩܪܝܒ ܝܬܝܪ ܡܢ ܣܦܩܐ ܓܘܒ̈ܝܐ". Drucker ܘ-Albrezzi (2026، ܦܐ̈ܬܐ 1-2) ܟܡܩܪܒܝ ܢܘܣܚܐ ܦܫܝܛܐ ܡܢ ܟܠ ܩܐ ܟܠ ܦܪܘܝܩܬ – ܚܘ̈ܡܪܐ + ܦܘܠܚܢܐ + ܚܘܝܐ + ܫܘܬܦܘܬܐ – ܗܕܡܐ ܪܒܝܥܝܐ ܚܕܬܐ ܝܠܗ ܓܘ ܡܦܩܬܐ ܬܪܝܢܝܬܐ: ܡܪ̈ܝ ܨܒܘܬܐ ܕܚܘܡܪܐ ܝܢ ܩܢܝܢܐ ܬܪܒܝܬܝܐ ܕܝܠܗܘܢ ܥܠܝܠܐ ܝܠܗ ܫܘܬܦ̈ܐ ܚܝ̈ܐ ܝܢܐ ܓܘ ܦܣ̈ܩܬܐ ܥܠ ܡܛܝܬܐ، ܡܦܠܚܢܘܬܐ، ܬܚܘܝܬܐ ܘܚܘܝܐ، ܘܐܢܫ̈ܐ ܕܐܘܡܢܘܬܐ ܘܬܠܡܝ̈ܕܐ ܓܘ ܓܘܕܐ ܙܕܩܝ̈ܐ ܝܢܐ ܠܝܕܥܬܐ ܘܠܫܘܒܚܐ – ܘܫܒܥܐ ܥܒ̈ܕܐ ܫܪ̈ܫܝܐ ܕܟܠ ܚܕ ܡܢܝܗܝ ܦܣܩܬܐ ܝܠܗ̇ ܘܠܐ ܕܪܓܐ ܐܘܡܢܝܐ: ܡܨܥܝܘܬܐ (ܫܘܢܝܐ ܠܕܝܓܝܛܠܝܐ)، "datafication" ܘܥܒܕܐ ܕܡܘܕܝܠ، ܦܘܠܚܢܐ ܘܦܘܫܩܐ، ܚܘܝܐ، rendering ܘܡܥܠܬܐ، ܩܝܡܘܬܐ ܘܢܛܪܬܐ، ܘܚܘܫ̈ܒܐ ܐܝܬܝܩܝ̈ܐ؛ "ܡܐܢ̈ܐ ܐܘܡܢܝ̈ܐ ܡܢ ܟܠ ܥܠܡ ܠܐ ܝܢܐ ܠܐ ܦܢܝ̈ܐ ܡܢ ܓܢܒܐ ܕܛܝ̈ܡܐ ܡܪ̈ܕܘܬܢܝܐ" (ܦܐܬܐ 2). ܘܡܐܡܪܐ ܪܫܝܐ ܕܝܠܗܘܢ ܝܠܗ ܥܠܬܐ ܕܟܠ ܓܢܣܐ ܓܘ ܨܘܪܬܐ ܟܦܬܚ ܒ"ܫܪܫܐ ܩܕܡ ܡܐܢܐ": "ܡܐܢ̈ܐ ܘܐܬܪ̈ܘܬܐ ܕܥܒܕܐ ܟܫܚܠܦܝ، ܐܠܐ ܫܪ̈ܫܐ ܕܥܒܕܐ ܕܝܓܝܛܠܝܐ ܓܠܝܠܗܘܢ ܘܩܡܠܗܘܢ" (ܦܐܬܐ 2) – ܐܝܢܐ ܕܟܝܕܥܐ ܕܒܢܝܐ ܪܫܝܡܬܐ ܕܩܫ̈ܬܐ (edge list) ܒܕ ܡܫܢܝܐ ܠܗ̇ ܠ-Gephi، ܠ-Cytoscape ܝܢ ܠܟܠ ܡܐ ܕܐܬܐ ܒܬܪܝܗܘܢ. Dawson (2020، ܦܐܬܐ 1) ܟܡܦܬܝܐ ܬܚܘܡܐ ܡܢ ܝܕ̈ܥܬܐ ܕܒܪܢܫܘܬܐ ܠܝܕ̈ܥܬܐ ܕܟܢܫܐ: "ܕܝܓܝܛܠܝܐ" ܫܡܐ ܓܘܢܝܐ ܝܠܗ ܩܐ ܐܘܪ̈ܚܬܐ ܕܟܟܢܫܝ ܘܟܦܫܩܝ ܝܗܝ̈ܒܬܐ ܒܐܘܪ̈ܚܬܐ ܕܚܘܫܒܢܐ – ܐܦ ܐܘܪ̈ܚܬܐ ܚܕ̈ܬܐ (ܝܘܠܦܢܐ ܕܡܟܝܢܐ، ܦܘܫܩܐ ܕܝܗܝ̈ܒܬܐ ܪ̈ܒܬܐ (big data)) ܘܐܦ ܥܬܝ̈ܩܬܐ ܕܫܚܠܦܠܗܘܢ (ܦܢܩܝܬܐ ܕܫܘܐ̈ܠܐ، ܡܫܐܠܬܐ، ܦܘܫܩܐ ܕܡܨܝ̈ܕܬܐ) – ܘܩܐ ܟܠ ܡܠܬܐ ܓܘ ܟܬܒܐ ܕܝܠܗ̇ ܐܝܬ ܦܣܩܐ ܕ"ܐܝܬܝܩܐ، ܡܪ̈ܕܘܬܐ ܘܢܡܘܣܐ" ܕܡܢܗ ܫܩܝܠ̈ܐ ܝܢܐ ܡܥܝܪ̈ܢܘܬܐ ܐܝܬܝܩ̈ܝܬܐ ܓܘ ܓܢ̈ܣܐ ܕܠܬܚܬ.
ܘܡܢ ܓܢܒܐ ܕܝܕ̈ܥܬܐ ܕܟܢܫܐ ܒܚܘܫܒܢܐ – ܬܪܝܢ ܟܬܒ̈ܐ ܕܝܘܠܦܢܐ. Cioffi-Revilla (2017، ܦܐܬܐ 2) ܟܡܚܕܕ ܚܩܠܐ ܐܝܟ "ܒܘܨܝܐ ܒܝܢܝ ܚܩ̈ܠܐ ܕܥܠܡܐ ܟܢܫܝܐ ܒܡܫܘ̈ܚܬܐ ܣܓܝ̈ܐܐ، ܡܢ ܥܒܘܕܐ ܝܚܝܕܝܐ ܗܠ ܟܢܘ̈ܫܝܐ ܪ̈ܒܐ ܡܢ ܟܠ، ܒܐܘܪܚܐ ܕܚܘܫܒܢܐ"، ܘܟܡܙܗܪ ܕܐܗܘ ܠܐ ܟܙܥܪ ܠܝܗܝ̈ܒܬܐ ܪ̈ܒܬܐ (big data)، ܠܦܘܫܩܐ ܕܡܨܝ̈ܕܬܐ ܝܢ ܠ-simulation – ܐܢܝ ܐܪܒܥܐ ܚܩ̈ܠܐ ܝܢܐ ܕܟܡܣܝܥܝ ܚܕ ܠܚܕ: ܡܦܩܬܐ ܒܚܘܕܝܗ ܕܝܕܥܬܐ، ܡܨܝ̈ܕܬܐ ܟܢܫ̈ܝܬܐ، ܣܒܝܟܘܬܐ ܟܢܫܝܬܐ ܘ-simulation ܟܢܫܝܐ (ܦܐ̈ܬܐ 12-17). ܐܗܐ ܝܠܗ̇، ܠܦܘܬ ܡ̈ܠܘܗܝ، "ܝܕܥܬܐ ܕܡܨܝܐ ܒܝܕ ܡܐܢ̈ܐ" ܐܝܟ ܝܕܥܬܐ ܕܟܘ̈ܟܒܐ ܒܬܪ ܛܠܣܩܘܦ – "ܡܐܢ̈ܐ ܐܢܝ ܝܢܐ ܡܐܢ̈ܐ ܪ̈ܫܝܐ ܕܒܗܘܢ ܝܕܥܬܐ ܟܒܢܝܐ ܝܕܥܬܐ ܚܕܬܐ" (ܦܐ̈ܬܐ 3-4) – ܘܐܗܐ ܝܠܗ̇ ܥܠܬܐ ܕܨܘܪܬܐ ܕܡܐܢ̈ܐ ܡܠܬܐ ܕܐܘܪܚܐ ܕܒܘܨܝܐ ܝܠܗ̇ ܘܠܐ ܐܘܡܢܝܬܐ. Salganik (2018، ܦܐ̈ܬܐ 6-8) ܟܝܗܒ ܙܘܓܐ ܕܟܡܛܟܣ ܓܢ̈ܣܐ ܕܟܢܫܐ: ܝܗܝ̈ܒܬܐ "ܡܛܝܒ̈ܬܐ ܡܢ ܩܕܡ" (readymades – ܥܩ̈ܒܬܐ ܕܫܪ̈ܟܘܬܐ ܘܫܘܠܛܢ̈ܐ ܒܢܝܠܗܘܢ ܩܐ ܢܝܫ̈ܐ ܐܚܪ̈ܢܐ، ܘܒܨܘܝܐ ܟܡܫܚܠܦ ܢܝܫܐ ܕܝܠܗܘܢ، ܐܝܟ Duchamp) ܩܘܒܠ ܝܗܝ̈ܒܬܐ "ܒܦܘܩܕܢܐ" (custommades – ܦܢܩܝܬܐ ܕܫܘܐ̈ܠܐ ܝܢ ܢܣܝܘܢܐ ܕܒܢܝ̈ܐ ܝܢܐ ܩܐ ܫܘܐܠܐ، ܐܝܟ Michelangelo)، ܘܒܘܨܝܐ ܕܡܬܒܥܝܢܐ ܡܢ ܟܠ ܝܠܗ "ܡܢܬܐ Duchamp ܘܡܢܬܐ Michelangelo". ܘܐܝܟ Drucker ܘ-Albrezzi، ܐܦ ܐܗܘ ܟܟܬܒ ܥܠ ܫܪ̈ܫܐ ܘܠܐ ܥܠ ܐܬܪ̈ܘܬܐ (platforms): "ܒܕܘܟܬܐ ܕܐܘܪܚܐ ܕܐܬܪܐ-ܒܬܪ-ܐܬܪܐ"، ܥܣܪܐ ܕܝܠܝ̈ܬܐ ܟܠܢܝ̈ܬܐ ܕܡܒܘ̈ܥܐ ܕܝܗܝ̈ܒܬܐ ܪ̈ܒܬܐ، ܕܒܕ ܦܐܝ̈ܐ ܗܘܝܢ ܐܦ ܩܐ "ܡܒܘ̈ܥܐ ܕܝܗܝ̈ܒܬܐ ܕܒܕ ܒܢܝ̈ܐ ܗܘܝܢ ܓܘ ܥܬܝܕܐ" (ܦܐܬܐ 17) – ܐܢܝ ܓܘ ܓܢܣܐ 7 ܝܢܐ.
ܝܕ̈ܥܬܐ ܕܒܪܢܫܘܬܐ ܕܝܓܝܛܠܝ̈ܬܐ
ܡܠܬܐ: ܡ̈ܠܐ، ܟܬܝܒܬܐ ܕܐܝܕܐ، ܒܝܬ ܟܬܒ̈ܐ، ܨܘܪܬܐ ܕܐܬܪܐ ܬܫܥܝܬܢܝܬܐ. ܫܘܐܠܐ ܛܘܦܣܢܝܐ: ܡܘܕܝ ܡܫܘܬܦܐ ܝܠܗ ܒܝܢܝ 3,000 ܬܫܥܝ̈ܬܐ ܕܚܕ ܐܢܫܐ ܠܐ ܒܕ ܩܪܐ ܠܟܠܗܝ؟ ܡܐܢ̈ܐ ܪ̈ܫܝܐ: corpus، TEI، ܡܨܝ̈ܕܬܐ، GIS ܬܫܥܝܬܢܝܐ.
ܝܕ̈ܥܬܐ ܕܟܢܫܐ ܒܚܘܫܒܢܐ
ܡܠܬܐ: ܥܘܒܕܐ، ܪܥܝܢܐ، ܐܣܘܪܐ ܟܢܫܝܐ، ܐܬܪܐ (platform). ܫܘܐܠܐ ܛܘܦܣܢܝܐ: ܕܟܝ ܟܡܬܦܪܣܐ ܫܡܥܬܐ ܓܘ ܡܨܝܕܬܐ ܕܡܠܝܘܢ ܡܦܠܚܢ̈ܐ؟ ܡܐܢ̈ܐ ܪ̈ܫܝܐ: API ܘ-scraping، ܦܘܫܩܐ ܟܡܝܝܐ ܕܡ̈ܠܐ، ܡܨܝ̈ܕܬܐ، simulation، ܝܘܠܦܢܐ ܕܡܟܝܢܐ (machine learning).
ܘܩܐ ܡܘܕܝ ܐܗܐ ܦܐܝܐ ܝܠܗ ܠܣܐܝܛ ܕܣܛܐܛܝܣܛܝܩܐ؟ ܡܛܠ ܕܣܛܐܛܝܣܛܝܩܐ ܝܠܗ̇ ܬܚܬܝܬܐ ܕܬܪܝܢ ܚܩ̈ܠܐ: topic modeling ܦܘܫܩܐ ܕܥܠ̈ܠܬܐ (factor analysis) ܝܠܗ ܥܠ ܡ̈ܠܐ، ܡܚܘܝܢܐ ܕܡܨܥܝܘܬܐ (centrality) ܣܛܐܛܝܣܛܝܩܐ ܡܚܘܝܢܝܬܐ (descriptive statistics) ܝܠܗ̇ ܥܠ ܐܣܘܪ̈ܐ، ܘ-simulation ܡܒܘܚܪܐ ܝܠܗ ܩܘܒܠ ܝܗܝ̈ܒܬܐ ܒܡܐܢ̈ܐ ܝܕ̈ܝܥܐ. ܐܝܢܐ ܕܟܝܕܥ ܕܩܪܐ ܡܐܛܪܝܟܣ ܕܐܣܘܪ̈ܐ ܕܚܕ̈ܕܐ (correlation matrix) ܟܝܕܥ ܕܩܪܐ ܡܐܛܪܝܟܣ ܕܩܘܪܒܐ (adjacency matrix).
ܕܟܝ ܟܩܪܚ ܠܘ̈ܚܐ
ܟܠ ܠܘܚܐ (table) ܟܡܚܘܐ ܡܐܢ̈ܐ ܕܚܕ ܓܢܣܐ ܓܘ ܚܡܫܐ ܥܡܘ̈ܕܐ. ܐܦܣܢܘܬܐ ܘܛܝܡܐ ܓܘ ܬܠܬܐ ܪ̈ܘܫܡܐ: ܪܡܙܐ ܦܬܝܚܐ – ܪܡܙܐ ܓܠܝܐ ܝܠܗ، ܡܓܢ، ܡܨܝܚ ܕܡܬܩܢܚ ܘܫܚܠܦܚ ܠܗ؛ ܡܓܢ (ܩܦܝܠܐ) ܝܢ ܡܓܢ + ܒܦܪܥܢܐ – ܡܓܢ ܩܐ ܡܦܠܚܢܘܬܐ ܐܠܐ ܪܡܙܐ ܩܦܝܠܐ ܝܠܗ، ܓܒ ܙܒ̈ܢܐ ܥܡ ܬܘܩ̈ܢܐ ܒܦܪܥܢܐ ܝܢ ܬܚܘ̈ܡܐ؛ ܒܦܪܥܢܐ – ܐܦܣܢܘܬܐ ܒܦܪܥܢܐ، ܪܘܒܐ ܕܙܒ̈ܢܐ ܥܡ ܛܝܡܐ ܩܐ ܡܕܪ̈ܫܝܬܐ ܝܢ ܐܦܣܢܘܬܐ ܕܩܡܦܘܣ. ܡܨܥܬܐ (interface): "ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ" – ܡܨܥܬܐ ܓܪܦܝܬܐ ܥܠ ܚܘܫܒܢܐ؛ "ܒܪܐܘܙܪ" – ܟܦܠܚ ܓܘ ܣܐܝܛ، ܕܠܐ ܬܘܩܢܐ؛ "ܪܡܙܐ" – ܟܬܒܘܬܐ ܕܪܡܙܐ (library) ܝܢ ܣܕܪܐ ܕܦܘܩ̈ܕܢܐ، ܟܒܥܐ R، Python ܝܢ Java.
ܐܣܘܪ̈ܐ (links)، ܐܦܣܢܘ̈ܝܬܐ ܘܐܝܟܢܝܘܬܐ ܕܡܦܬܚܢܘܬܐ ܕܟܠ 99 ܡܐܢ̈ܐ ܡܒܘܚܪ̈ܐ ܝܢܐ ܩܘܒܠ ܣܐܝ̈ܛܐ ܕܡܐܢ̈ܐ ܓܘ ܐܝܠܘܠ 2026. ܡܐܢܐ ܕܠܐ ܡܬܦܬܚ ܬܘܒ ܪܫܝܡܐ ܝܠܗ ܓܘ ܡܥܝܪ̈ܢܘܬܐ؛ ܡܐܢܐ ܕܦܠܝܛܐ ܝܠܗ – ܡܛܠ ܕܠܐ ܡܨܐ ܗܘܐ ܕܡܫܪܪܚ ܠܗ، ܠܐ ܡܛܠ ܕܠܐ ܝܠܗ ܛܒܐ.
1. ܦܘܫܩܐ ܕܡ̈ܠܐ ܘܚܦܪܬܐ ܕܡ̈ܠܐ (text mining)
ܓܢܣܐ ܪܒܐ ܡܢ ܟܠ ܓܘ ܬܪܝܢ ܚܩ̈ܠܐ، ܘܐܦ ܕܘܟܬܐ ܕܓܘܗ̇ ܦܘܪܫܢܐ ܒܝܢܬܝܗܘܢ ܓܠܝܐ ܝܠܗ. ܓܘ ܝܕ̈ܥܬܐ ܕܒܪܢܫܘܬܐ ܕܝܓܝܛܠܝ̈ܬܐ ܟܡܡܠܠܝ ܥܠ "ܩܪܝܢܐ ܡܢ ܪܚܩܐ" (distant reading; Moretti, 2013; Jockers, 2013): ܡܢܝܢܐ ܕܡ̈ܠܐ، concordance ܘ-topic modeling (topic modeling) ܥܠ corpus ܕܪܒܐ ܝܠܗ ܡܢ ܕܡܨܝܚ ܕܩܪܝܚ ܠܗ. ܓܘ ܝܕ̈ܥܬܐ ܕܟܢܫܐ ܒܚܘܫܒܢܐ ܟܡܡܠܠܝ ܥܠ "ܡ̈ܠܐ ܐܝܟ ܝܗܝ̈ܒܬܐ" (text as data; Grimmer, Roberts & Stewart, 2022): ܡ̈ܠܐ ܡܫܬܚܠܦܢܐ (variable) ܝܢܐ، ܘܟܠ ܫܪܟܐ – ܡܫܘܚܬܐ، ܫܪܝܪܘܬܐ (reliability) ܘܬܪܝܨܘܬܐ (validity) – ܐܝܟ ܓܘ ܟܠ ܒܘܨܝܐ ܟܡܝܝܐ. ܡܐܢ̈ܐ ܡܫܘܬܦ̈ܐ ܝܢܐ؛ ܦܘܪܫܢܐ ܓܘ ܫܘܐܠܐ ܝܠܗ.
ܫܪܫܐ ܩܕܡ ܡܐܢܐ. Drucker (2021, Section 7a): ܦܣ̈ܩܬܐ ܡܘܕܝ ܡܨܝܚ ܕܡܫܚܚ (ܕܥܒܕܚ ܦܪܡܝܛܪ)، ܕܡܢܚ، ܕܛܟܣܚ ܘܕܡܚܘܚ "ܥܒ̈ܕܐ ܕܦܘܫܩܐ ܝܢܐ ܕܟܓܒܠܝ ܦܐܪ̈ܐ ܕܒܘܨܝܐ"؛ ܓܘ ܡܦܩܬܐ ܬܪܝܢܝܬܐ ܐܗܐ ܟܡܬܩܪܝܐ parametrization – ܐܝܬ ܕܝܠܝ̈ܬܐ ܕܒܦܫܝܩܘܬܐ ܟܗܘܝܐ ܡܚܘܝܢܐ (index / measure) (ܡܢܝܢܐ ܕܡ̈ܠܐ، ܐܘܪܟܐ ܕܡܕܪܫܐ)، ܘܣܓܝ̈ܐܐ ܐܚܪ̈ܢܐ "ܓܡܝܪܐܝܬ ܡܬܩܪܝ̈ܢܐ ܝܢܐ ܩܐ ܣܘܟܠܐ ܐܢܫܝܐ" ܘܥܡ ܟܠ ܗܕܐ ܥܣܩܐ ܝܠܗ ܕܥܒܕܚ ܠܗܘܢ ܦܪܡܝܛܪ، ܘܐܦ ܡܘܕܝ ܥܠܝܠܐ ܝܠܗ ܓܘ ܝܗܝ̈ܒܬܐ ܘܕܟܝ ܡܬܩܢܐ ܝܠܗ ܟܒܥܐ "ܚܘܪܐ ܒܩܘܪܬܢܝܐ" (Drucker & Albrezzi, 2026, pp. 14, 49). ܘܠܫܢܐ ܕܡܐܢ̈ܐ ܟܡܛܫܐ ܐܗܐ: topic modeling ܡܬܚܙܝܐ ܝܠܗ ܐܝܟ ܕ"ܟܡܦܩ" ܡ̈ܠܐ ܪ̈ܫܝܬܐ ܡܢ ܡ̈ܠܐ، "ܐܝܟ ܕܡ̈ܠܐ ܪ̈ܫܝܬܐ ܡܢ ܩܕܡ ܐܝܬܠܗܘܢ ܓܘ ܡ̈ܠܐ ܘܠܐ ܒܢܝ̈ܐ ܝܢܐ ܐܝܟ ܥܒܕܐ ܕܩܪܝܢܐ ܘܦܘܫܩܐ" (ܦܐܬܐ 51). ܡܬܠܐ ܙܥܘܪܐ ܘܚܪܝܦܐ ܡܢ ܡܦܩܬܐ ܩܕܡܝܬܐ: ܪܘܒܐ ܕܡܐܢ̈ܐ ܟܫܩܠܝ "stop words" ܐܝܟ ܐܬ̈ܘܬܐ ܕܝܕܥܬܐ، ܐܠܐ ܦܘܪܫܢܐ ܒܝܢܝ "האל" ܘ"אל" ܝܠܗ ܟܠ ܦܘܪܫܢܐ (Drucker, 2021, Section 7a). ܘܐܘܠܨܢܐ ܕܬܘܪܨܐ ܕܦܐܪ̈ܐ (reproducibility): ܪ̈ܗܛܐ ܡܬܢ̈ܝܐ ܕܚܦܪܬܐ ܕܡ̈ܠܐ ܘܦܘܫܩܐ ܬܪܒܝܬܝܐ "ܟܕܥܪܝ ܦܐܪ̈ܐ ܕܙܝܥܠܗܘܢ ܘܫܚܠܦܠܗܘܢ"، ܡܛܠ ܕ-corpus ܠܐ ܝܠܗ ܩܝܡܐ ܘܡܛܠ ܕܦܘܠܚܢܐ ܡܣܬܒܪܢܝܐ ܝܠܗ (ܦܐܬܐ 54) – ܘܡܛܠ ܗܕܐ ܙܪܥܐ (random seed) ܓܕܫܢܝܐ، ܢܘܣܚܐ ܘܦܪ̈ܡܝܛܪܐ ܡܢܬܐ ܝܢܐ ܡܢ ܡܫܟܚܢܘܬܐ. ܡܢ ܓܢܒܐ ܚܘܫܒܢܝܐ-ܟܢܫܝܐ، Cioffi-Revilla (2017، ܦܐ̈ܬܐ 13-14) ܟܩܪܐ ܠܐܗܐ ܓܢܣܐ "ܡܦܩܬܐ ܒܚܘܕܝܗ ܕܝܕܥܬܐ" ܘܟܚܙܐ ܠܗ ܐܝܟ "ܐܘܪܚܐ ܫܪܫܝܬܐ" ܕܚܩܠܐ، ܡܛܠ ܕܐܗܘ ܟܡܣܝܥ ܠܟܠ ܫܪܟܐ؛ ܘܓܘ ܦܘܠܚܢܐ ܕܚܦܪܬܐ ܕܝܗܝ̈ܒܬܐ ܕܝܠܗ (ܦܐ̈ܬܐ 115-117) ܫܘܐܠܐ ܩܕܡ ܡܐܢܐ ܝܠܗ – ܥܠ ܣܪܛܐ ܒܝܢܝ ܫܘܐܠܐ ܕܡܬܕܒܪ ܒܝܕ ܝܗܝ̈ܒܬܐ (inductive) ܘܫܘܐܠܐ ܕܡܬܕܒܪ ܒܝܕ ܬܐܘܪܝܐ (deductive) – ܘ"ܢܘܣܚܐ ܕܫܘܐ̈ܠܐ ܕܒܘܨܝܐ ܣܢܝܩ ܝܠܗ ܕܚܕܪ ܟܠ ܒܘܨܝܐ ܕܚܦܪܬܐ ܕܝܗܝ̈ܒܬܐ، ܡܛܠ ܕܫܘܐ̈ܠܐ ܕܒܘܨܝܐ ܟܦܣܩܝ ܟܠ ܚܕ ܡܢ ܕܪ̈ܓܐ ܕܒܬܪܗ"؛ ܘܩܕܡ ܦܘܫܩܐ (analysis) – ܣܩܢܐ (OCR)، ܡܕܟܝܢܘܬܐ (cleaning)، ܡܨܠܠܢܘܬܐ، ܦܘܪܩܐ ܠܚܕܝ̈ܘܬܐ (ܓܢܣܐ ܕܒܬܪܗ). ܐܝܬܝܩܐ ܘܢܡܘܣܐ (Dawson, 2020, pp. 79-85): ܚܦܪܬܐ ܕܝܗܝ̈ܒܬܐ "ܕܝܕܥܐ ܠܦܘܠܓܐ ܕܐܢܫ̈ܐ" – Berendt ܘ-Preibusch (2017, as cited in Dawson) ܟܡܚܘܝ ܕܟܝ ܦܘܠܓܐ ܕܐܢܫ̈ܐ ܟܗܘܐ ܡܢ "ܡܥܒܕܢܘܬܐ ܡܚܠܛܬܐ ܕܫܘܠܡܐ ܐܢܫܝܐ ܘܡܟܝܢܝܐ"؛ ܘܓܘ ܚܘܝܕܐ ܐܘܪܘܦܝܐ ܘܓܘ ܒܪܝܛܢܝܐ ܐܝܬ "ܙܕܩܐ ܕܓܙܐ ܕܝܗܝ̈ܒܬܐ" ܥܠ ܟܢܘ̈ܫܝܐ ܕܒܥܝܐ ܗܘܐ ܠܥܡܠܐ ܪܒܐ ܓܘ ܟܢܫܐ ܕܝܠܗܘܢ، ܘܦܘܫܩܐ ܚܘܫܒܢܝܐ ܕܚܘܡܪܐ ܢܛܝܪܐ ܬܡܢ ܫܠܝܛܐ ܝܠܗ ܒܣ ܩܐ ܢܝܫ̈ܐ ܠܐ ܬܓܪ̈ܝܐ – ܐܝܢܐ ܕܟܚܦܪ corpus ܢܛܝܪܐ ܣܢܝܩ ܝܠܗ ܕܒܚܪ ܢܡܘܣܐ ܐܬܪܢܝܐ.
ܥܒܪܝܐ ܐܝܬܠܗ̇ ܐܘܠܨܢܐ ܕܒܢܝܢܐ: ܪܘܒܐ ܕܡܐܢ̈ܐ ܡܬܦܬܚ̈ܐ ܝܢܐ ܩܐ ܐܢܓܠܝܙܝܐ ܘܟܣܒܪܝ ܕܡܠܬܐ = ܣܕܪܐ ܕܐܬ̈ܘܬܐ ܒܝܢܝ ܦܬܝ̈ܘܬܐ، ܐܝܡܢ ܕܓܘ ܥܒܪܝܐ "וכשהלכנו" ܐܪܒܥܐ ܚܕܝ̈ܘܬܐ ܝܢܐ. ܡܐܢܐ ܕܟܐܡܪ "ܐܝܬ ܥܘܕܪܢܐ ܩܐ ܥܒܪܝܐ" ܪܘܒܐ ܕܙܒ̈ܢܐ ܒܣ tokenization ܟܒܥܐ؛ ܦܘܪܩܐ ܡܘܪܦܘܠܘܓܝܐ ܫܪܝܪܐ ܣܢܝܩ ܝܠܗ ܠܡܐܢ̈ܐ ܕܓܘ ܠܘܚܐ 3.
ܠܘܚܐ 1. ܦܘܫܩܐ ܕܡ̈ܠܐ ܘܚܦܪܬܐ ܕܡ̈ܠܐ
| ܡܐܢܐ | ܡܘܕܝ ܟܥܒܕ | ܐܦܣܢܘܬܐ ܘܛܝܡܐ | ܡܨܥܬܐ | ܡܥܝܪ̈ܢܘܬܐ (notes) |
|---|---|---|---|---|
| Voyant Tools | ܕܘܟܬܐ ܕܩܪܝܢܐ ܘܦܘܫܩܐ ܓܘ ܒܪܐܘܙܪ: ܥܢܢܐ ܕܡ̈ܠܐ (word cloud)، ܨܠܝ̈ܢܐ (trends)، concordance ܘܐܣܘܪ̈ܐ – ܕܠܐ ܬܘܩܢܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ | ܢܘܩܙܐ ܕܫܘܪܝܐ ܦܫܝܩܐ ܡܢ ܟܠ. ܡ̈ܠܐ ܟܡܫܬܕܪܝ ܠܣܝܪܒܪ؛ ܩܐ ܚܘܡܪܐ ܪܓܝܫܐ – VoyantServer ܐܬܪܢܝܐ (ܗܘ ܡܐܢܐ، ܥܠ ܚܘܫܒܢܐ). |
| AntConc | ܩܘܦܬܐ ܕܡܐܢ̈ܐ ܩܐ ܝܕܥܬܐ ܕܠܫܢܐ ܕ-corpus: KWIC، collocations، n-grams، ܡ̈ܠܐ ܪ̈ܫܝܬܐ (keywords). | ܡܓܢ (ܩܦܝܠܐ) | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ | ܛܘܦܣܐ ܓܘ ܝܘܠܦܢܐ ܕܝܕܥܬܐ ܕܠܫܢܐ ܕ-corpus. ܢܘܣܚܐ 4.4 (2026). ܠܐ ܝܠܗ ܪܡܙܐ ܦܬܝܚܐ – ܬܘܟܢܝܬܐ ܡܓܢ ܕܡܬܥܕܪܐ ܒܡܘܗܒ̈ܬܐ. |
| Sketch Engine | ܐܬܪܐ (platform) ܐܘܡܢܝܐ ܕ-corpus: word sketches، collocations، ܡܦܩܬܐ ܕܫܡ̈ܗܐ ܐܘܡܢ̈ܝܐ (terms)، corpora ܡܛܝܒ̈ܐ ܓܘ 100+ ܠܫܢ̈ܐ. | ܒܦܪܥܢܐ | ܒܪܐܘܙܪ | ܥܒܪܝܐ ܐܝܬܠܗ̇ ܥܘܕܪܢܐ ܥܡ part-of-speech tagging ܘ-lemmatization. ܡܢܘܝ (subscription) ܡܕܪܫܝܐ ܝܚܝܕܝܐ ܡܢ ܩܪܝܒ 7 ܝܘܪܘ ܒܝܪܚܐ؛ 30 ܝܘ̈ܡܐ ܕܢܣܝܘܢܐ. |
| MALLET | topic modeling (LDA)، ܦܘܪܫܐ ܠܓܢ̈ܣܐ (classification) ܕܟܬܒ̈ܐ ܘ-sequence tagging – ܡܢ ܣܕܪܐ ܕܦܘܩ̈ܕܢܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܡܐܢܐ ܩܠܐܣܝܩܝܐ ܩܐ topic modeling ܓܘ ܝܕ̈ܥܬܐ ܕܒܪܢܫܘܬܐ. Java؛ ܢܘܣܚܐ 2.1 (2026). |
| spaCy | ܟܬܒܘܬܐ ܕܪܡܙܐ (library) ܕ-NLP ܬܘܥܡܠܝܬܐ ܓܘ Python: tokenization، tagging، ܦܘܫܩܐ ܕ-syntax، ܡܫܬܘܕܥܢܘܬܐ ܕܫܡ̈ܗܐ (named entities). | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܥܒܪܝܐ – ܒܣ tokenization، ܕܠܐ ܡܘܕܝܠ (model) ܡܠܦܐ. ܩܐ ܦܘܠܚܢܐ ܓܡܝܪܐ ܕܥܒܪܝܐ ܚܙܝܡܘܢ ܠܘܚܐ 3. |
| NLTK | ܟܬܒܘܬܐ ܕܪܡܙܐ ܕܝܘܠܦܢܐ ܕ-NLP ܓܘ Python، ܥܡ 50+ corpora ܘܡܕܒܪܢܐ (guide) ܦܬܝܚܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܕܘܟܬܐ ܕܝܘܠܦܢܐ ܕܚܘܫ̈ܒܐ؛ ܩܐ ܥܒܕܐ ܒܡܫܘܚܬܐ ܪܒܬܐ – spaCy. |
| quanteda | ܛܘܦܣܐ ܕ-R ܩܐ ܦܘܫܩܐ ܟܡܝܝܐ ܕܡ̈ܠܐ: corpus، ܡܐܛܪܝܟܣ ܕܟܬܒܐ-ܡܠܬܐ (document-term matrix)، ܠܟܣܝ̈ܩܘܢܐ (dictionaries)، ܡܘܕܝ̈ܠܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܓܘܒܝܐ ܛܒܝܥܝܐ ܩܐ ܐܝܢܐ ܕܡܢ ܩܕܡ ܟܦܠܚ ܓܘ R ܩܐ ܣܛܐܛܝܣܛܝܩܐ. ܟܡܬܚܠܛ ܥܡ stm ܘ-topicmodels. |
| CATMA | ܪܘܫܡܐ ܒܐܝܕܐ ܘܒܫܘܬܦܘܬܐ (annotation) ܕܡ̈ܠܐ ܕܣܦܪܘܬܐ، ܥܡ ܦܘܫܩܐ ܘ-visualization ܕܪ̈ܘܫܡܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܒܪܐܘܙܪ | ܦܘܫܩܐ ܐܝܟܝܐ-ܦܘܫܩܝܐ (qualitative-interpretive)، ܠܐ ܟܡܝܝܐ-ܒܚܘܕܝܗ. ܓܘ ܣܐܝܛ ܐܝܬ ܡܕܒܪܢܐ ܒܥܒܪܝܐ (ܩܐ ܢܘܣܚܐ ܥܬܝܩܐ). TU Darmstadt. |
| LIWC-22 | ܦܘܫܩܐ ܕܢܦܫܐ-ܕܠܫܢܐ (psycholinguistic): 100+ ܡܫܘ̈ܚܬܐ ܕܠܟܣܝܩܘܢ (ܪܓܫܐ، ܚܘܫܒܐ (cognition)، ܦܪܨܘܦܐ ܩܕܡܝܐ ܘܐܚܪ̈ܢܐ). | ܒܦܪܥܢܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܪܡܙܐ | ܡܐܢܐ ܡܩܒܠܐ ܓܘ ܝܕܥܬܐ ܕܢܦܫܐ ܕܠܫܢܐ. ܠܟܣܝܩܘܢ ܥܒܪܝܐ ܠܐ ܥܠܝܠܐ ܝܠܗ؛ ܐܦܣܢܘܬܐ ܡܕܪܫܝܬܐ ܦܪܝܫܬܐ ܝܠܗ̇ ܡܢ ܬܓܪܝܬܐ. |
ܡܥܝܪܢܘܬܐ. ܐܦܣܢܘܬܐ ܘܐܝܟܢܝܘܬܐ ܡܒܘܚܪ̈ܐ ܝܢܐ ܩܘܒܠ ܣܐܝ̈ܛܐ ܕܡܐܢ̈ܐ ܓܘ ܐܝܠܘܠ 2026. "ܥܘܕܪܢܐ ܩܐ ܥܒܪܝܐ" ܪܫܝܡܐ ܝܠܗ ܒܣ ܐܝܡܢ ܕܣܐܝܛ ܒܢܦܫܗ ܟܐܡܪ ܥܠܗ.
2. ܪܡܙܢܘܬܐ ܕܡ̈ܠܐ، OCR ܘܒܝܬ ܟܬܒ̈ܐ ܕܝܓܝܛܠܝܐ
ܩܕܡ ܕܦܫܩܚ ܡ̈ܠܐ ܣܢܝܩ ܝܠܗ ܕܐܝܬ ܡ̈ܠܐ. ܬܠܬܐ ܕܪ̈ܓܐ ܩܕܡ ܦܘܫܩܐ (analysis): ܫܘܢܝܐ ܕܨܘܪܬܐ ܕܣܩܢܐ ܝܢ ܕܟܬܝܒܬܐ ܕܐܝܕܐ ܠܡ̈ܠܐ (OCR ܩܐ ܡܛܒܥܐ، HTR ܩܐ ܟܬܝܒܬܐ ܕܐܝܕܐ)، ܪܡܙܢܘܬܐ (coding) ܕܒܢܝܢܐ ܘܕܦܘܫܩܐ ܓܘ ܛܘܦܣܐ ܦܬܝܚܐ (TEI – ܛܘܦܣܐ ܕܡܦܩ̈ܬܐ ܝܕ̈ܥܢܝܬܐ ܕܝܓܝܛܠܝ̈ܬܐ)، ܘܛܘܟܣܐ ܕܚܘܡܪܐ ܕܒܝܬ ܟܬܒ̈ܐ ܒܢܦܫܗ. ܢܡܘܣܐ ܕ-FAIR (Wilkinson et al., 2016) – ܝܗܝ̈ܒܬܐ ܕܡܨܝܚ ܕܡܫܟܚܚ، ܕܡܛܝܚ، ܕܚܠܛܚ ܘܕܡܦܠܚܚ ܬܘܒ – ܟܫܪܐ ܠܐܟܐ: ܐܣܟܝܡܐ ܦܬܝܚܐ ܕܡܨܝܚ ܕܡܦܩܚ ܛܒ ܝܠܗ ܡܢ ܡܐܢܐ ܫܦܝܪܐ ܕܟܩܦܠ ܚܘܡܪܐ.
ܫܪܫܐ ܩܕܡ ܡܐܢܐ. Drucker ܘ-Albrezzi (2026، ܦܐܬܐ 15) ܟܡܩܫܝ ܥܠ ܚܕܐ ܡܠܬܐ: ܝܗܝ̈ܒܬܐ ܠܐ ܝܢܐ "ܝܗܝ̈ܒܬܐ" (data، "ܡܐ ܕܝܗܝܒܐ ܝܠܗ") ܐܠܐ "ܫܩܝܠ̈ܬܐ" – capta – "ܝܕܥܬܐ ܕܐܚܝܕܬܐ ܝܠܗ̇ ܓܘ ܦܘܠܚܢܐ ܕܦܫܝܛܘܬܐ (abstraction) ܘܒܢܝܢܐ ܕܬܠܝܐ ܝܠܗ ܒܦܣ̈ܩܬܐ ܕܡܢ ܩܕܡ ܥܒ̈ܕܐ ܕܦܘܫܩܐ ܝܢܐ"؛ ܡܛܠ ܗܕܐ ܡܘܕܝܠ (model) ܕܝܗܝ̈ܒܬܐ – ܡܘܕܝ ܡܢܝܐ ܝܠܗ، ܡܘܢܐ ܝܠܗ̇ ܚܕܝܘܬܐ، ܡܘܕܝ ܫܕܝܐ ܝܠܗ – ܣܢܝܩ ܝܠܗ ܕܗܘܝܐ ܟܬܝܒܐ ܐܝܟ ܟܠ ܦܣܩܬܐ ܕܐܘܪܚܐ ܕܒܘܨܝܐ (ܦܐܬܐ 18: "ܝܗܝ̈ܒܬܐ ܡܢ ܟܠ ܥܠܡ ܠܐ ܝܢܐ ܠܐ ܦܢܝ̈ܐ، ܐܠܐ ܟܠ ܐܡܢ ܒܢܝ̈ܐ ܝܢܐ ܡܢ ܚܕ ܚܙܘܐ ܦܪܝܫܐ"). ܘܥܠ ܠܫܢ̈ܐ ܕܪܘܫܡܐ (markup) (ܦܐܬܐ 35): ܝܘܬܪܢܐ ܕܝܠܗܘܢ ܝܠܗ ܕܟܫܩܠܝ ܬܪܝܢܘܬܐ ܕܣܘܟܠܐ (ambiguity) – ܘܐܗܐ ܐܦ ܚܣܝܪܘܬܐ ܕܝܠܗܘܢ ܝܠܗ̇، ܡܛܠ ܕ"ܚܘܫܒ̈ܢܐ ܠܐ ܟܣܝܒܪܝ ܬܪܝܢܘܬܐ ܕܣܘܟܠܐ" ܐܝܡܢ ܕܪܘܒܐ ܕܚܘܡܪܐ ܕܝܕ̈ܥܬܐ ܕܒܪܢܫܘܬܐ ܡܠܝܐ ܝܠܗ ܡܢܗ̇؛ ܪܡܙܢܘܬܐ ܒ-TEI ܕܡܬܠܐ ܕܐܦ ܐܡܝܪܬܐ ܕܡ̈ܠܐ ܝܠܗ̇ ܟܐܡܪܐ ܓܘܒܝܐ، ܘܐܢܝ ܟܫܐܠܝ ܐܢ ܐܝܬ ܓܘܗ ܐܘܠܨܢܐ ܐܝܬܝܩܝܐ ܘܟܦܢܝ: "ܫܪܝܪܐܝܬ". ܐܣܟܝ̈ܡܐ ܕܦܐܝ̈ܠܐ ܘܥܝ̈ܕܐ ܕܫܡ̈ܗܐ ܦܣܝܩ̈ܐ ܝܢܐ ܓܘ ܕܪܓܐ ܕܬܘܩܢܐ، ܥܡ ܫܘܬܦ̈ܐ ܕܡܕܪ̈ܫܝܬܐ ܕܒܕ ܢܛܪܝ ܚܘܡܪܐ (ܦܐܬܐ 27). ܐܝܬܝܩܐ ܘܢܡܘܣܐ: ܝܗܝ̈ܒܬܐ ܕܝܪ̈ܬܘܬܐ (legacy data) – ܝܗܝ̈ܒܬܐ ܕܒܢܝܠܗܘܢ ܐܢܫܐ ܐܚܪܢܐ، ܓܒ ܙܒ̈ܢܐ ܕܠܐ ܟܬܝܒܬܐ، ܘܦܣ̈ܩܬܐ ܡܘܕܝ ܟܢܝܫܐ، ܕܟܝܐ ܘܫܩܝܠܐ ܝܠܗ "ܒܠܟܝ ܠܐ ܡܨܝܚ ܕܡܬܥܒܕ̈ܢ ܬܘܒ"؛ ܕܡܢܘ ܝܢܐ ܝܗܝ̈ܒܬܐ، ܐܝܢܝ ܐܦܣܢܘ̈ܝܬܐ ܣܢܝܩ̈ܐ ܗܘܘ ܩܐ ܒܢܝܢܐ ܕܝܠܗܘܢ، ܘܡܘܕܝ ܥܡ ܓܢܝܙܘܬܐ (privacy) – ܡܦܠܚܢܘܬܐ ܬܢܝܢܬܐ ܕܪܫܝܡܬܐ ܝܢ ܕܓܙܐ ܥܬܝܩܐ ܠܐ ܟܡܦܨܐ ܡܢ ܐܢܝ ܫܘܐ̈ܠܐ (ܦܐ̈ܬܐ 15-16، 42).
ܠܘܚܐ 2. ܪܡܙܢܘܬܐ ܕܡ̈ܠܐ، OCR ܘܒܝܬ ܟܬܒ̈ܐ ܕܝܓܝܛܠܝܐ
| ܡܐܢܐ | ܡܘܕܝ ܟܥܒܕ | ܐܦܣܢܘܬܐ ܘܛܝܡܐ | ܡܨܥܬܐ | ܡܥܝܪ̈ܢܘܬܐ (notes) |
|---|---|---|---|---|
| TEI Guidelines | ܛܘܦܣܐ ܕ-XML ܩܐ ܪܡܙܢܘܬܐ ܕܡ̈ܠܐ ܓܘ ܝܕ̈ܥܬܐ ܕܒܪܢܫܘܬܐ: ܒܢܝܢܐ، ܢܘ̈ܣܚܐ، ܡܥܝܪ̈ܢܘܬܐ، ܫܡ̈ܗܐ (entities). | ܪܡܙܐ ܦܬܝܚܐ | ܛܘܦܣܐ (ܠܐ ܬܘܟܢܝܬܐ) | P5 ܢܘܣܚܐ 4.12 (2026). ܠܐ ܝܠܗ ܬܘܟܢܝܬܐ – ܦܘܪܫܐ (specification)؛ ܫܘܪܝܐ ܛܒܐ: TEI by Example. |
| oXygen XML Editor | ܡܬܩܢܢܐ (editor) ܐܘܡܢܝܐ ܕ-XML ܥܡ ܥܘܕܪܢܐ ܒܢܝܐ ܓܘܗ ܩܐ TEI، XSLT ܘ-XQuery ܘܚܘܝܐ ܚܙܝܐ ܕܬܘܩܢܐ. | ܒܦܪܥܢܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ | ܛܘܦܣܐ ܓܘ ܦܪܘܝ̈ܩܬܐ ܕܡܦܩ̈ܬܐ. ܐܦܣܢܘܬܐ ܡܕܪܫܝܬܐ ܒܛܝܡܐ ܒܨܝܪܐ (ܛܝܡܐ ܠܦܘܬ ܫܘܐܠܐ). |
| TEI Publisher | ܡܦܪܣܡܢܘܬܐ ܕܡܦܩܬܐ ܕܝܓܝܛܠܝܬܐ ܡܢ ܦܐܝܠ TEI: ܚܘܝܐ، ܒܨܝܐ، ܡܦܩܬܐ (export) – ܕܠܐ ܟܬܝܒܬܐ ܕܣܐܝܛ ܡܢ ܫܘܪܝܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ / ܪܡܙܐ | ܢܘܣܚܐ 11 (ܐܝܠܘܠ 2026). ܟܒܥܐ ܣܝܪܒܪ (eXist-db) ܝܢ ܕܘܟܬܐ ܡܕܪܫܝܬܐ. |
| Transkribus | ܦܘܫܩܐ ܕܟܬܝܒ̈ܬܐ ܕܐܝܕܐ ܘܕܟܬܒ̈ܐ ܬܫܥܝܬܢ̈ܝܐ ܒܥܘܕܪܢܐ ܕܡܘܕܝ̈ܠܐ ܡܠܦ̈ܐ؛ ܡܨܝܚ ܕܡܠܦܚ ܡܘܕܝܠ ܩܐ ܟܬܝܒܬܐ ܕܐܝܕܐ ܦܪܝܫܬܐ. | ܡܓܢ + ܒܦܪܥܢܐ | ܒܪܐܘܙܪ | 50 credits ܡܓܢ ܒܝܪܚܐ؛ Scholar 99 ܝܘܪܘ ܒܫܢܬܐ. ܡܘܕܝ̈ܠܐ ܩܐ ܥܒܪܝܐ/ܝܝܕܝܫ ܐܝܬ ܐܠܐ ܩܠܝܠ̈ܐ ܝܢܐ. ܚܘܡܪܐ ܟܣܠܩ ܠܣܝܪܒܪ. |
| eScriptorium | ܚܠܦܐ ܦܬܝܚܐ ܕ-Transkribus: segmentation، ܬܘܪܓܡܐ ܕܐܬ̈ܘܬܐ (transcription) ܘܝܘܠܦܢܐ ܕܡܘܕܝ̈ܠܐ ܕ-HTR (ܡܫܩܠܢܐ Kraken). | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ | ܟܒܥܐ ܬܘܩܢܐ ܡܕܪܫܝܐ ܝܢ ܣܝܪܒܪ ܕܝܠܘܟܘܢ. ܡܬܦܬܚܐ ܝܠܗ ܓܘ EPHE؛ ܡܦܠܚܐ ܝܠܗ ܓܘ ܦܪܘܝ̈ܩܬܐ ܕܟܬܝܒ̈ܬܐ ܕܐܝܕܐ ܥܒܪ̈ܝܬܐ (Sofer Mahir). |
| Tesseract OCR | ܡܫܩܠܢܐ ܦܬܝܚܐ ܕ-OCR، 100+ ܠܫܢ̈ܐ ܥܡ ܥܒܪܝܐ، ܡܢ ܣܕܪܐ ܕܦܘܩ̈ܕܢܐ ܝܢ ܐܝܟ ܟܬܒܘܬܐ ܕܪܡܙܐ (library). | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܫܬܐܣܐ ܕܪܘܒܐ ܕܡܐܢ̈ܐ ܕ-OCR ܡܓܢ̈ܝܐ. ܐܝܟܝܘܬܐ ܓܘ ܥܒܪܝܐ ܡܛܒܥܬܐ ܛܒܬܐ ܝܠܗ̇؛ ܩܐ ܟܬܝܒܬܐ ܕܐܝܕܐ – ܠܐ. |
| Omeka S | ܐܬܪܐ (platform) ܩܐ ܡܦܪܣܡܢܘܬܐ ܕܟܢܘ̈ܫܝܐ ܕܝܓܝܛܠܝ̈ܐ ܘܚܘܝ̈ܐ ܓܘ ܫܒܝܟܬܐ ܥܡ ܡܝܛܐ-ܝܗܝ̈ܒܬܐ (metadata) ܐܣܝܪ̈ܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ | ܟܒܥܐ ܕܘܟܬܐ ܕ-PHP ܕܝܠܘܟܘܢ (Omeka.net – ܬܫܡܫܬܐ ܡܐܘܚܕܬܐ ܦܪܝܫܬܐ). ܡܕܪ̈ܫܝܬܐ ܣܓܝ̈ܐܐ ܟܡܪܗܛܝ ܚܕ ܢܘܣܚܐ. |
| Tropy | ܛܘܟܣܐ، ܬܚܘܝܬܐ ܘܪܘܫܡܐ ܕܨܘܪ̈ܬܐ ܕܟܬܒ̈ܐ ܡܢ ܒܝܬ ܟܬܒ̈ܐ – ܥܠ ܚܘܫܒܢܐ، ܠܐ ܓܘ ܥܢܢܐ (cloud). | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ | ܡܐܢܐ ܩܐ ܒܨܘܝܐ ܕܟܕܥܪ ܡܢ ܒܝܬ ܟܬܒ̈ܐ ܥܡ 3,000 ܨܘܪ̈ܬܐ. ܡܦܩܬܐ (export) ܠ-Omeka S، JSON-LD ܘ-CSV. |
ܡܥܝܪܢܘܬܐ. TEI ܛܘܦܣܐ ܝܠܗ ܘܠܐ ܬܘܟܢܝܬܐ؛ oXygen ܝܠܗ ܡܬܩܢܢܐ (editor) ܡܩܒܠܐ ܩܐ ܥܒܕܐ ܓܘܗ، ܘ-TEI Publisher – ܐܘܪܚܐ ܩܐ ܡܦܪܣܡܢܘܬܐ ܕܡܦܩܬܐ.
3. ܥܒܪܝܐ، ܝܗܘܕܝܘܬܐ ܘܠܫܢ̈ܐ ܩܠܐܣܝܩ̈ܝܐ
ܓܢܣܐ ܕܓܘܗ "ܡܐܢܐ ܩܕܡܝܐ ܓܘ ܥܠܡܐ" ܠܐ ܝܠܗ ܡܢ ܟܠ ܐܡܢ ܡܐܢܐ ܫܪܝܪܐ. ܥܒܪܝܐ – ܕܟܬܒܐ ܩܕܝܫܐ، ܕܪ̈ܒܢܐ (Hazal) ܘܚܕܬܐ – ܠܫܢܐ ܥܬܝܪܐ ܝܠܗ̇ ܒܡܘܪܦܘܠܘܓܝܐ ܥܡ ܟܬܝܒܬܐ ܕܠܐ ܢܘ̈ܩܙܐ، ܘܟܠ ܦܘܫܩܐ ܪܨܝܢܐ ܟܫܪܐ ܒܦܘܪܩܐ ܡܘܪܦܘܠܘܓܝܐ ܕܡܐܢ̈ܐ ܟܠܢ̈ܝܐ ܠܐ ܟܥܒܕܝ. ܓܢܒ ܡܐܢ̈ܐ ܕܦܘܠܚܢܐ – ܓܙ̈ܐ ܕܝܗܝ̈ܒܬܐ: ܡ̈ܠܐ ܝܗܘܕ̈ܝܐ ܩܠܐܣܝܩ̈ܝܐ ܐܕܝܘܡ ܪܡܝܙ̈ܐ ܝܢܐ ܩܪܝܒܐܝܬ ܓܡܝܪܐܝܬ ܘܦܬܝܚ̈ܐ ܠ-API، ܘܥܬܝܪܘܬܐ ܕܡܘܕܥܢܘܬܐ (press) ܥܒܪܝܬܐ ܬܫܥܝܬܢܝܬܐ ܡܨܝܐ ܕܡܒܘܨܝܐ ܓܡܝܪܐܝܬ. ܓܘ ܫܘܠܡܐ ܕܠܘܚܐ – ܬܠܬܐ ܡܒܘ̈ܥܐ ܩܐ ܣܢܣܩܪܝܬ ܘܩܐ ܠܫܢ̈ܐ ܩܠܐܣܝܩ̈ܝܐ، ܩܐ ܒܨܘܝܐ ܕܟܦܠܚ ܒܦܘܚܡܐ.
ܫܪܫܐ ܩܕܡ ܡܐܢܐ. ܠܐܟܐ ܫܪܫܐ ܕ-Drucker ܘ-Albrezzi ܥܠ ܬܪܝܢܘܬܐ ܕܣܘܟܠܐ (2026، ܦܐܬܐ 35) ܟܦܠܚ ܥܦܝܦܐܝܬ: ܟܬܝܒܬܐ ܕܠܐ ܢܘ̈ܩܙܐ ܬܪܝܢܘܬܐ ܕܣܘܟܠܐ ܒܢܝܬܐ ܝܠܗ̇ ܓܘ ܟܠ token، ܘܦܘܪܩܐ ܡܘܪܦܘܠܘܓܝܐ ܦܣܩܬܐ ܝܠܗ ܕܡܐܢܐ ܟܥܒܕ ܒܕܘܟܬܘܟܘܢ. ܘܩܐ ܓܙ̈ܐ ܕܪܫܝܡ̈ܐ ܝܢܐ – ܐܝܢܐ ܕܟܣܡܟ ܥܠ BHSA ܟܝܪܬ ܡܘܕܝܠ (model) ܠܫܢܝܐ ܕ-ETCBC؛ ܡܘܕܝ ܚܬܝܬܐܝܬ، ܓܘ ܦܣܩܐ 6 ܕܦܐܬܐ NLP ܒܠܫܢܐ ܥܒܪܝܐ.
ܠܘܚܐ 3. ܥܒܪܝܐ، ܝܗܘܕܝܘܬܐ ܘܠܫܢ̈ܐ ܩܠܐܣܝܩ̈ܝܐ
| ܡܐܢܐ | ܡܘܕܝ ܟܥܒܕ | ܐܦܣܢܘܬܐ ܘܛܝܡܐ | ܡܨܥܬܐ | ܡܥܝܪ̈ܢܘܬܐ (notes) |
|---|---|---|---|---|
| DICTA | ܡܪܟܙܐ ܩܐ ܦܘܫܩܐ ܕܡ̈ܠܐ ܥܒܪ̈ܝܐ: ܡܢܩܙܢܐ ܒܚܘܕܝܗ (automatic vocalizer)، ܒܨܝܐ ܓܘ ܣܦܪܘܬܐ ܕܪ̈ܒܢܐ (Hazal)، ܡܘܕܝ̈ܠܐ ܕܠܫܢܐ ܩܐ ܥܒܪܝܐ ܚܕܬܐ ܘܕܪ̈ܒܢܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ / ܪܡܙܐ | ܕܘܟܬܐ ܩܕܡܝܬܐ ܩܐ ܦܘܠܚܢܐ ܕܥܒܪܝܐ. ܪܡܙܐ ܓܘ GitHub؛ ܣܐܝܛ ܣܡܝܟܐ ܝܠܗ ܥܠ JavaScript ܘܟܒܥܐ ܒܪܐܘܙܪ ܓܡܝܪܐ. |
| HebPipe | ܨܢܘܪܐ (pipeline) ܓܡܝܪܐ ܕ-NLP ܩܐ ܥܒܪܝܐ ܓܘ Python: segmentation، tagging، lemmatization، ܦܘܫܩܐ ܕ-syntax، ܫܡ̈ܗܐ (entities)، coreference. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܢܘܣܚܐ 4.0 (2025)، pip install hebpipe. ܦܘܫܪܐ ܓܡܝܪܐ ܡܢ ܟܠ ܒܪܡܙܐ ܦܬܝܚܐ ܩܐ ܥܒܪܝܐ ܚܕܬܐ. |
| YAP | ܦܘܪܩܐ ܡܘܪܦܘܠܘܓܝܐ ܘܦܘܫܩܐ ܕ-syntax ܡܚܠܛ̈ܐ ܩܐ ܥܒܪܝܐ ܚܕܬܐ (ܡܥܒܕܬܐ ONLP، Bar-Ilan). | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܠܠܟܣܝܩܘܢ ܕ-Ben-Gurion ܐܦܣܢܘܬܐ ܦܪܝܫܬܐ. ܕܠܐ ܚܘܕܬܐ ܡܢ 2019 – ܬܘܒ ܟܦܠܚ. |
| AlephBERT | ܡܘܕܝܠ ܕܠܫܢܐ BERT ܩܐ ܥܒܪܝܐ، ܩܐ ܬܘܪܨܐ (fine-tuning) ܠܥܒ̈ܕܐ ܕܦܘܪܫܐ ܠܓܢ̈ܣܐ ܘܡܦܩܬܐ ܕܝܕܥܬܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | 2021؛ ܡܘܕܝ̈ܠܐ ܚܕ̈ܬܐ ܝܬܝܪ ܩܐ ܥܒܪܝܐ – ܓܘ DICTA. ܟܒܥܐ ܝܕܥܬܐ ܕ-transformers. |
| Sefaria | ܒܝܬ ܟܬܒ̈ܐ ܕܡ̈ܠܐ ܝܗܘܕ̈ܝܐ ܐܣܝܪ̈ܐ – ܟܬܒܐ ܩܕܝܫܐ (Tanakh)، Talmud، Midrash، Halakha – ܥܡ ܬܘܪ̈ܓܡܐ ܘ-API ܦܬܝܚܐ. | ܡܓܢ (ܩܦܝܠܐ) | ܒܪܐܘܙܪ / ܪܡܙܐ | ܪܘܒܐ ܕܡ̈ܠܐ ܓܘ ܐܦܣܢܘܬܐ ܦܬܝܚܬܐ ܝܢܐ ܘܡܦܩ̈ܐ ܝܢܐ ܓܘ GitHub؛ ܐܦܣܢܘܬܐ ܟܫܚܠܦܐ ܡܢ ܟܬܒܐ ܠܟܬܒܐ. ܬܪܥܐ ܕܡܦܬܚ̈ܢܐ: developers.sefaria.org. |
| ܦܪܘܝܩܬ Ben-Yehuda | ܣܦܪܘܬܐ ܥܒܪܝܬܐ ܕܓܘ ܕܘܟܬܐ ܕܥܡܐ (public domain) – ܩܪܝܒ 66,000 ܥܒ̈ܕܐ – ܥܡ API. | ܡܓܢ (ܩܦܝܠܐ) | ܒܪܐܘܙܪ / ܪܡܙܐ | ܩܠܝܕܐ ܕ-API ܡܓܢ ܒܬܫܡܫܬܐ ܕܝܠܘܟܘܢ (50 ܒܥܘ̈ܬܐ ܒܩܛܝܢܐ). ܡܢܬܐ ܡܢ ܥܒ̈ܕܐ – ܒܐܦܣܢܘܬܐ، ܠܐ ܓܘ ܕܘܟܬܐ ܕܥܡܐ. |
| Ma'agarim – ܠܟܣܝܩܘܢ ܬܫܥܝܬܢܝܐ | corpus ܕܠܟܣܝܩܘܢ ܬܫܥܝܬܢܝܐ ܕܐܩܕܡܝܐ ܕܠܫܢܐ ܥܒܪܝܐ: ܒܨܝܐ ܠܦܘܬ ܡܠܬܐ، ܫܪܫܐ ܘܡܫܩܠܐ ܓܘ ܟܠ ܙܒ̈ܢܐ ܕܥܒܪܝܐ. | ܡܓܢ (ܩܦܝܠܐ) | ܒܪܐܘܙܪ | ܡܨܥܬܐ (interface) ܒܥܒܪܝܐ ܒܣ؛ ܠܝܬ API. ܡܒܘܥܐ ܩܐ ܬܫܥܝܬܐ ܕܡܠܬܐ. |
| ܡܘܕܥܢܘܬܐ (press) ܝܗܘܕܝܬܐ ܬܫܥܝܬܢܝܬܐ (JPress) | ܡܘܕܥܢܘܬܐ (press) ܥܒܪܝܬܐ ܘܝܗܘܕܝܬܐ ܕܣܩܝܢܬܐ ܘܕܡܨܝܐ ܕܡܒܘܨܝܐ ܓܡܝܪܐܝܬ (ܒܝܬ ܟܬܒ̈ܐ ܐܘܡܬܢܝܐ ܘܡܕܪܫܬܐ ܥܠܝܬܐ ܕܬܠ-ܐܒܝܒ). | ܡܓܢ (ܩܦܝܠܐ) | ܒܪܐܘܙܪ | ܡܘܢܥܐ ܥܬܝܩܐ jpress.nli.org.il ܠܐ ܟܦܠܚ – ܡܦܠܚܘܢ ܒܐܗܐ ܐܣܘܪܐ (link). ܐܬܪܐ (platform) Veridian. |
| ܦܪܘܝܩܬ Responsa (Bar-Ilan) | ܓܙܐ ܕܣܦܪܘܬܐ ܕܐܘܪܝܬܐ ܘ-100,000+ ܦܘܢ̈ܝܐ (responsa)، ܐܣܝܪܐ ܘܕܡܨܐ ܕܡܒܘܨܝܐ. | ܒܦܪܥܢܐ | ܒܪܐܘܙܪ | ܡܢܘܝ (subscription)؛ ܛܝܡܐ ܠܦܘܬ ܫܘܐܠܐ. ܡܨܥܝ̈ܬܐ (interfaces) ܒܥܒܪܝܐ، ܐܢܓܠܝܙܝܐ ܘܦܪܢܣܝܐ. |
| Perseus Digital Library | ܡ̈ܠܐ ܝܘܢ̈ܝܐ ܘܠܛܝ̈ܢܝܐ ܥܡ ܬܘܪ̈ܓܡܐ، ܠܟܣܝ̈ܩܘܢܐ ܘܡܐܢ̈ܐ ܕܦܘܫܩܐ؛ ܟܥܒܪ ܠܕܘܟܬܐ ܕ-Scaife Viewer. | ܡܓܢ (ܩܦܝܠܐ) | ܒܪܐܘܙܪ | ܕܘܟܬܐ ܕܩܪܝܢܐ ܚܕܬܐ: scaife.perseus.org. |
| CLTK | ܟܬܒܘܬܐ ܕܪܡܙܐ (library) ܕ-Python ܩܐ ܦܘܠܚܢܐ ܕܠܫܢ̈ܐ ܕܩܕܡ ܙܒܢܐ ܚܕܬܐ: ܠܛܝܢܝܐ، ܝܘܢܝܐ، ܣܢܣܩܪܝܬ، ܥܒܪܝܐ ܥܬܝܩܬܐ ܘܐܚܪ̈ܢܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܢܘܣܚܐ 2.5 (2026)، Python 3.13+. ܥܘܡܩܐ ܕܟܣܝܘܬܐ ܟܫܚܠܦ ܡܢ ܠܫܢܐ ܠܠܫܢܐ. |
| Digital Corpus of Sanskrit | corpus ܕܣܢܣܩܪܝܬ ܡܦܪܩܐ ܡܢ sandhi ܘܪܫܝܡܐ ܒܡܘܪܦܘܠܘܓܝܐ (ܩܪܝܒ 4.6 ܡܠܝܘܢ̈ܐ ܕܡ̈ܠܐ). | ܡܓܢ (ܩܦܝܠܐ) | ܒܪܐܘܙܪ | ܣܐܝܛ ܒ-HTTP ܒܣ، ܕܠܐ ܪܘܫܡܐ ܕܐܦܣܢܘܬܐ ܝܢ ܕܝܘܡܐ ܕܚܘܕܬܐ. ܝܗܝ̈ܒܬܐ ܐܦ ܓܘ GitHub (OliverHellwig/sanskrit). |
| GRETIL | ܪܫܝܡܬܐ ܕܡ̈ܠܐ ܐܠܩܛܪܘܢ̈ܝܐ ܒܣܢܣܩܪܝܬ، ܦܐܠܝ، ܛܡܝܠܝ ܘܛܝܒܬܝ، ܪܡܝܙ̈ܐ ܒ-TEI (Göttingen). | ܡܓܢ (ܩܦܝܠܐ) | ܒܪܐܘܙܪ | ܚܘܕܬܐ ܐܚܪܝܬܐ 2020؛ ܡܢܬܐ ܡܢ ܐܣܘܪ̈ܐ ܕܫܪܫܐ ܠܐ ܟܦܠܚܝ. ܬܘܒ ܓܙܐ ܪܫܝܐ ܩܐ ܡܚܬܬܐ ܕܡ̈ܠܐ. |
| Sanskrit Heritage (INRIA) | ܠܟܣܝܩܘܢ، ܦܫܘܩܐ ܡܘܪܦܘܠܘܓܝܐ ܘܦܪܘܩܐ ܕ-sandhi ܩܐ ܣܢܣܩܪܝܬ (Gérard Huet). | ܡܓܢ (ܩܦܝܠܐ) | ܒܪܐܘܙܪ | ܣܐܝܛ ܟܡܢܥ ܡܛܝܬܐ ܒܚܘܕܝܗ – ܡܫܪܪܐ ܝܠܗ ܡܢ ܦܐܬܐ ܕ-INRIA ܕܟܬܘܒܐ؛ ܒܚܘܪܘܢ ܓܘ ܒܪܐܘܙܪ. ܪܡܙܐ ܓܘ gitlab.inria.fr. |
ܡܥܝܪܢܘܬܐ. ܡܐܢ̈ܐ ܥܒܪ̈ܝܐ ܩܪܝܒܐܝܬ ܟܠܗܘܢ ܡܓܢ̈ܝܐ ܝܢܐ؛ ܦܪܘܝܩܬ Responsa ܦܠܛܬܐ ܝܠܗ̇ ܒܦܪܥܢܐ. YAP ܘ-AlephBERT ܠܐ ܟܡܬܚܕܬܝ ܡܢ 2019-2021 – ܦܥܠ̈ܐ ܝܢܐ ܐܠܐ ܣܢܝܩ ܝܠܗ ܠܒܘܚܪܢܐ ܕܚܠ̈ܦܐ ܓܘ DICTA.
4. ܦܘܫܩܐ ܕܡܨܝ̈ܕܬܐ (network analysis)
ܦܘܫܩܐ ܕܡܨܝ̈ܕܬܐ ܟܢܫ̈ܝܬܐ (social network analysis) ܝܠܗ ܣܘܟܐ ܥܬܝܩܐ ܡܢ ܟܠ ܕܝܕ̈ܥܬܐ ܕܟܢܫܐ ܒܚܘܫܒܢܐ – sociometry ܡܢ ܕܪܐ ܕ-20 ܕܩܒܠܠܗ̇ ܚܝܠܐ ܕܚܘܫܒܢܐ. ܫܘܐܠܐ ܕܝܠܗ ܦܪܝܫܐ ܝܠܗ ܡܢ ܫܘܐܠܐ ܣܛܐܛܝܣܛܝܩܝܐ ܥܡܝܐ: ܠܐ "ܡܘܕܝ ܟܡܚܘܐ ܠܦܪܨܘܦܐ" ܐܠܐ "ܡܘܕܝ ܟܡܚܘܐ ܠܐܣܘܪ̈ܐ". ܓܘ ܝܕ̈ܥܬܐ ܕܒܪܢܫܘܬܐ ܗܢܝ ܡܐܢ̈ܐ ܟܡܦܠܚܝ ܩܐ ܡܨܝ̈ܕܬܐ ܕܐܓܪ̈ܬܐ، ܩܐ ܦܪ̈ܨܘܦܐ ܓܘ ܬܫܥܝܬܐ ܘܩܐ ܡܬ̈ܝܬܐ ܒܝܢܝ ܟܬܒ̈ܐ.
ܓܘܒܝܐ ܥܒܕܢܝܐ: Gephi ܩܐ visualization ܘܒܘܨܝܐ، ܟܬܒܘܬܐ ܕܪܡܙܐ (igraph ܝܢ NetworkX) ܩܐ ܡܚܘ̈ܝܢܐ ܘܩܐ ܣܛܐܛܝܣܛܝܩܐ، ܘ-UCINET ܐܢ ܡܕܒܪܢܐ (guide) ܕܝܘܟܘܢ Borgatti ܝܠܗ. ܩܐ ܡܨܝ̈ܕܬܐ ܕܟܬܒ̈ܐ (bibliometric) – VOSviewer.
ܫܪܫܐ ܩܕܡ ܡܐܢܐ. ܡܘܕܝܠ (model) ܕܝܗܝ̈ܒܬܐ ܕܡܨܝܕܬܐ ܢܘܣܚܐ ܝܠܗ ܕܬܠܬܐ ܗܕ̈ܡܐ – ܡܠܬܐ-ܐܣܘܪܐ-ܡܠܬܐ – ܕܡܨܝܚ ܕܒܢܚ ܠܗ ܓܘ ܓܠܝܘܢܐ (sheet) ܘܕܡܦܩܚ ܠܗ ܠܟܠ ܐܬܪܐ؛ ܥܒܕܐ ܫܪܝܪܐ ܝܠܗ ܚܬܝܬܘܬܐ ܕܙܢܐ ܕܐܣܘܪܐ (ܠܐ ܚܕ "ܐܣܝܪܐ ܠ" ܩܐ ܟܠ ܡܕܡ) ܘܕܫܘܢܝܐ ܓܘ ܙܒܢܐ (Drucker & Albrezzi, 2026, p. 70). Cioffi-Revilla (2017، ܦܐܬܐ 147) ܟܚܬܬ ܦܘܪܫܢܐ: "graphs ܠܡܨܝ̈ܕܬܐ ܐܝܟ ܡܘܕܝ̈ܠܐ ܕܬܐܘܪܝܐ ܕܦܣ̈ܩܬܐ ܠܦܣܩܬܐ ܕܦܣ̈ܩܬܐ ܝܢܐ" – graph ܚܘܝܐ ܝܠܗ، ܠܐ ܡܨܝܕܬܐ؛ ܡܨܝܕܬܐ ܓܘܕܐ ܡܣܝܟܬܐ ܝܠܗ̇ ܕܡ̈ܠܐ (nodes) ܘܓܘܕܐ ܕܐܣܘܪ̈ܐ (edges) ܕܡܚܕܕܐ ܝܠܗ̇ ܥܠܗ̇، ܘܐܢܝ ܬܪܝܢ ܬܚܘ̈ܡܐ ܐܢܝ ܝܢܐ ܥܒܕܐ. ܘܥܠ ܬܘܟܢܝܬܐ (ܦܐ̈ܬܐ 168-169): UCINET ܝܠܗ̇ "ܚܕܐ ܡܢ ܨܪ̈ܪܐ ܕܬܘܟܢܝܬܐ ܕܡܬܚܙܝܢ ܝܬܝܪ ܡܢ ܟܠ"، ܘܡܨܝ̈ܕܬܐ ܕܡܐܐ ܘܐܠܦ̈ܐ ܕܡ̈ܠܐ ܒܣ ܓܘ ܫܢ̈ܐ ܐܚܪ̈ܝܐ ܗܘܝܠܗܘܢ ܕܡܨܝܚ ܕܡܬܥܒܕ̈ܢ – ܙܒܢܐ ܕܚܘܫܒܢܐ ܘܡܨܝܐܘܬܐ (tractability) ܚܘܫ̈ܒܐ ܝܢܐ ܩܕܡ ܓܘܒܝܐ ܕܡܚܘܝܢܐ. Dawson (2020، ܦܐ̈ܬܐ 356-361) ܟܡܘܣܦܐ ܫܘܐ̈ܠܐ ܕܬܪܝܨܘܬܐ (validity): ܕܟܝ ܟܡܙܕܩܚ ܬܚܘܡܐ ܕܡܨܝܕܬܐ؛ ܡܘܕܝ ܟܥܒܕܐ ܝܕܥܬܐ ܚܣܝܪܬܐ ܥܠ ܐܢܫ̈ܐ ܘܐܣܘܪ̈ܐ ܠܡܣܒ ܒܐܦ̈ܐ (bias) ܕܡܚܘ̈ܝܢܐ؛ ܘܐܢ visualization ܝܠܗ ܐܘܪܚܐ ܬܪܝܨܬܐ ܩܐ ܦܘܫܩܐ ܕܕܝܠܝ̈ܬܐ ܕܒܢܝܢܐ – "ܡܨܐ ܚܘܝܐ ܚܙܝܐ ܕܡܚܘܐ ܠܗܘܢ ܒܛܥܝܘܬܐ؟" (ܦܘܢܝܐ: ܐܝܢ، ܘܡܛܠ ܗܕܐ ܡܚܘ̈ܝܢܐ ܓܘ igraph ܘܠܐ ܒܥܝܢܐ). ܐܝܬܝܩܐ ܘܢܡܘܣܐ (ܬܡܢ): ܐܝܢܐ ܕܟܡܚܘܐ ܡܨܝܕܬܐ ܕܝܠܗ ܝܗܒܠܗ ܫܠܡܘܬܐ – ܐܚܪ̈ܢܐ ܓܘ ܡܨܝܕܬܐ ܠܐ؛ ܠܐ ܝܕܝܥܘܬܐ (anonymity) ܡܨܝܐ ܕܬܒܪܐ ܒܣ ܡܢ ܕܘܟܬܐ ܓܘ ܡܨܝܕܬܐ؛ ܘܦܘܫܩܐ ܕܡܨܝܕܬܐ ܕܬܘܩܢܐ (organization) ܡܨܐ ܕܡܕܒܪ ܠܦܠܛܬܐ ܡܢ ܥܒܕܐ ܝܢ ܠܚܒܠܐ – "ܡܨܐ ܗܘܐ ܕܦܘܫܩܐ ܕܝܘܟ ܥܒܕ ܚܒܠܐ ܠܦܪ̈ܨܘܦܐ؟" ܫܘܐܠܐ ܝܠܗ ܕܟܡܫܬܐܠ ܩܕܡ ܟܢܫܐ.
ܠܘܚܐ 4. ܦܘܫܩܐ ܕܡܨܝ̈ܕܬܐ
| ܡܐܢܐ | ܡܘܕܝ ܟܥܒܕ | ܐܦܣܢܘܬܐ ܘܛܝܡܐ | ܡܨܥܬܐ | ܡܥܝܪ̈ܢܘܬܐ (notes) |
|---|---|---|---|---|
| Gephi | ܬܘܟܢܝܬܐ ܕܚܘܫܒܢܐ (desktop) ܩܐ visualization ܘܒܘܨܝܐ ܕܡܨܝ̈ܕܬܐ ܪ̈ܒܬܐ؛ Gephi Lite – ܢܘܣܚܐ ܕܒܪܐܘܙܪ. | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܒܪܐܘܙܪ | ܢܘܣܚܐ 0.11 (2026). ܡܐܢܐ ܡܩܒܠܐ ܩܐ ܚܘܝܐ ܕܡܨܝܕܬܐ؛ ܡܚܘ̈ܝܢܐ ܣܛܐܛܝܣܛܝܩ̈ܝܐ – ܓܘ ܟܬܒܘܬܐ ܕܪܡܙܐ. |
| Cytoscape | ܐܬܪܐ (platform) ܕܡܨܝ̈ܕܬܐ ܕܪܒܐ ܓܘ ܒܝܘܠܘܓܝܐ، ܟܠܢܝܐ ܓܡܝܪܐܝܬ، ܥܡ 100+ ܬܘܣܦ̈ܬܐ (plugins). | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܒܪܐܘܙܪ | Java. ܚܝܠܢܐ ܝܬܝܪ ܓܘ ܡܨܝ̈ܕܬܐ ܕܣܓܝ ܬܚܬܝ̈ܬܐ (multilayer) ܘܓܘ ܚܘܠܛܐ ܕܝܗܝ̈ܒܬܐ ܕܠܒܪ ܥܡ ܡ̈ܠܐ (nodes). |
| NetworkX | ܟܬܒܘܬܐ ܕܪܡܙܐ ܕ-Python ܩܐ ܒܢܝܢܐ، ܦܘܫܩܐ ܘܡܫܘܚܬܐ ܕܡܨܝ̈ܕܬܐ – ܡܨܥܝܘܬܐ (centrality)، communities، ܫܒ̈ܝܠܐ (paths). | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܢܘܣܚܐ 3.6 (2025). ܡܬܝܢܐ ܝܠܗ ܓܘ ܡܨܝ̈ܕܬܐ ܕܡܠܝܘܢ̈ܐ ܕܡ̈ܠܐ (nodes) – ܬܡܢ igraph. |
| igraph | ܟܬܒܘܬܐ ܕܪܡܙܐ ܕܡܨܝ̈ܕܬܐ ܡܣܪܗܒܬܐ ܥܡ ܡܨܥܝ̈ܬܐ (interfaces) ܩܐ R، Python، C ܘ-Mathematica. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܢܘܣܚܐ ܕ-R ܛܘܦܣܐ ܝܠܗ ܓܘ ܝܕ̈ܥܬܐ ܕܟܢܫܐ؛ ܟܡܬܚܠܛ ܥܡ statnet ܘ-ggraph. |
| Pajek | ܦܘܫܩܐ ܘ-visualization ܕܡܨܝ̈ܕܬܐ ܪ̈ܒܬܐ ܒܣܓܝ (Windows). | ܡܓܢ (ܩܦܝܠܐ) | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ | ܣܐܝܛ ܒ-HTTP ܒܣ؛ ܚܘܕܬܐ ܐܚܪܝܬܐ ܕܡܫܪܪܐ ܝܠܗ̇ – 2017. ܬܘܒ ܡܬܝܬܐ ܝܠܗ ܓܘ ܟܬܒ̈ܐ؛ ܡܓܢ ܩܐ ܡܦܠܚܢܘܬܐ ܠܐ ܬܓܪܝܬܐ. |
| UCINET | ܨܪܪܐ ܩܠܐܣܝܩܝܐ ܕܦܘܫܩܐ ܕܡܨܝ̈ܕܬܐ ܟܢܫ̈ܝܬܐ ܥܡ NetDraw ܩܐ visualization (Windows). | ܡܓܢ (ܩܦܝܠܐ) | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ | ܢܘܣܚܐ 6.847 (2026). ܡܐܢܐ ܕ-Borgatti، Everett ܘ-Freeman؛ ܓܘ Mac – ܒ-emulation. |
| VOSviewer | ܒܢܝܢܐ ܕܡܨܝ̈ܕܬܐ ܕܟܬܒ̈ܐ (bibliometric) – ܫܘܬܦܘܬܐ ܕܟܬܘ̈ܒܐ، ܡܬ̈ܝܬܐ، ܫܡ̈ܗܐ ܐܘܡܢ̈ܝܐ ܡܫܘܬܦ̈ܐ – ܘ-visualization ܕܝܠܗܘܢ. | ܡܓܢ (ܩܦܝܠܐ) | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܒܪܐܘܙܪ | ܢܘܣܚܐ 1.6.21 (2026). ܚܙܝܡܘܢ: ܣܐܝܛ ܡܬܬܒܪܐ ܗܘܐ (hacked) ܒ-31.8.2026 ܘܦܐܝܠ ܒܝܫܐ ܡܬܦܪܣܡܐ ܗܘܐ ܩܐ ܙܒܢܐ ܟܪܝܐ – ܡܚܬܘܢ ܒܣ ܡܢ ܣܐܝܛ ܪܫܡܝܐ ܘܒܚܘܪܘܢ (scan) ܡܚ̈ܬܬܐ ܕܗܘ ܙܒܢܐ. |
| nodegoat | ܕܘܟܬܐ ܕܒܘܨܝܐ ܓܘ ܫܒܝܟܬܐ ܩܐ ܝܗܝ̈ܒܬܐ ܕܐܣܘܪ̈ܐ ܓܘ ܝܕ̈ܥܬܐ ܕܒܪܢܫܘܬܐ: ܡܨܝܕܬܐ، ܨܘܪܬܐ ܕܐܬܪܐ ܘܣܪܛܐ ܕܙܒܢܐ (timeline) ܥܠ ܗܢܝ ܝܗܝ̈ܒܬܐ. | ܡܓܢ + ܒܦܪܥܢܐ | ܒܪܐܘܙܪ | ܚܘܫܒܢܐ (account) ܝܚܝܕܝܐ ܡܓܢ (ܫܘܪܪܐ ܩܪܝܒ 48 ܫܥ̈ܐ)؛ ܢܘܣܚܐ ܡܕܪܫܝܐ ܒܦܪܥܢܐ. ܪܡܙܐ ܦܬܝܚܐ ܝܠܗ، ܬܫܡܫܬܐ ܡܐܘܚܕܬܐ ܝܠܗ̇ (hosted). |
| Palladio | ܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ، graph ܘܪܫܝܡܬܐ ܕܝܗܝ̈ܒܬܐ ܬܫܥܝܬܢ̈ܝܬܐ ܕܠܘ̈ܚܐ – ܡܣܪܗܒܐ، ܓܘ ܒܪܐܘܙܪ، ܕܠܐ ܚܘܫܒܢܐ (account). | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ | Stanford. ܟܦܠܚ ܐܠܐ ܕܠܐ ܡܦܬܚܢܘܬܐ ܡܢ 2019 – ܛܒܐ ܝܠܗ ܩܐ ܒܘܨܝܐ ܩܕܡܝܐ، ܠܐ ܩܐ ܦܪܘܝܩܬ ܕܙܒܢܐ ܐܪܝܟܐ. |
ܡܥܝܪܢܘܬܐ. Palladio ܐܝܬܠܗ ܘܟܦܠܚ ܐܠܐ ܠܐ ܝܠܗ ܡܬܦܬܚܐ ܡܢ 2019. UCINET ܗܘܝܠܗ ܬܘܟܢܝܬܐ ܡܓܢ (ܣܐܝܛ ܬܘܒ ܟܡܚܘܐ ܐܣܘܪܐ (link) ܥܬܝܩܐ ܕ'buy').
5. GIS ܘܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ ܬܫܥܝܬܢ̈ܝܬܐ
ܛܟܣ̈ܐ ܕܝܕܥܬܐ ܓܐܘܓܪܦܝܬܐ (GIS) ܟܦܢܝ ܥܠ ܫܘܐܠܐ ܕ"ܐܝܟܐ": ܣܦܪܐ ܩܘܒܠ ܡܨܥܬܐ، ܦܘܠܓܐ (distribution) ܕܦܘܢ̈ܝܐ ܠܦܘܬ ܦܢܝܬܐ ܣܛܐܛܝܣܛܝܩܝܬܐ، ܨܘܪܬܐ ܕܐܬܪܐ ܬܫܥܝܬܢܝܬܐ ܕܣܝܡܬܐ ܝܠܗ̇ ܥܠ ܨܘܪܬܐ ܕܐܕܝܘܡ. ܩܐ ܒܨܘܝܐ ܟܢܫܝܐ ܓܘ ܐܝܣܪܐܝܠ ܐܝܬ ܬܪܝܢ ܡܒܘ̈ܥܐ ܡܓܢ̈ܝܐ ܚܫܝܚ̈ܐ ܝܬܝܪ: ܬܚܬܝ̈ܬܐ ܕܦܢܝ̈ܬܐ ܣܛܐܛܝܣܛܝܩ̈ܝܬܐ ܕܒܝܬ ܡܢܝܢܐ ܡܪܟܙܝܐ ܕܣܛܐܛܝܣܛܝܩܐ (CBS) – ܚܕܝܘܬܐ ܕܒܗ̇ ܟܡܬܦܪܣܡܝ ܝܗܝ̈ܒܬܐ ܕܡܢܝܢܐ ܕܥܡܐ (census) ܘܕܛܒܬܐ – ܘ-GovMap، ܬܪܥܐ ܐܘܡܬܢܝܐ ܕܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ. ܚܘܠܛܐ ܕܦܐܝܠ ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ (survey) ܥܡ ܬܚܬܝܬܐ ܕܦܢܝ̈ܬܐ ܣܛܐܛܝܣܛܝܩ̈ܝܬܐ ܝܠܗ ܕܪܓܐ ܕܟܡܥܒܪ ܦܘܫܩܐ ܡܢ "ܠܦܘܬ ܡܬܐ" ܠ"ܠܦܘܬ ܫܒܒܘܬܐ".
ܡܐܢܐ ܪܫܝܐ ܝܠܗ QGIS – ܚܠܦܐ ܡܓܢ ܓܡܝܪܐ ܕ-ArcGIS. ܩܐ ܦܘܫܩܐ ܣܛܐܛܝܣܛܝܩܝܐ-ܕܐܬܪܐ (spatial autocorrelation، spatial regression) – GeoDa.
ܫܪܫܐ ܩܕܡ ܡܐܢܐ. "ܟܠ ܛܟܣ̈ܐ ܕܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ ܣܡܝܟ̈ܐ ܝܢܐ ܥܠ ܛܠܠ̈ܐ (projections) ܕܟܡܫܚܠܦܝ ܐܣܟܝܡܐ ܕܬܠܬܐ ܡܫܘ̈ܚܬܐ ܠܚܘܝܐ ܕܬܪܬܝܢ ܡܫܘ̈ܚܬܐ ܘܐܝܬ ܓܘܝܗܝ ܥܘ̈ܩܡܐ"، ܘܣܒܪ̈ܐ ܕܒܢܝ̈ܐ ܝܢܐ ܓܘ ܚܘܝܐ ܣܢܝܩ̈ܐ ܝܢܐ ܕܗܘܝܝ ܓܠܝ̈ܐ ܓܘ ܡܐܡܪܐ ܕܨܘܪܬܐ ܟܡܫܡܫܐ (Drucker & Albrezzi, 2026, p. 77)؛ "ܫܬܐܣ̈ܐ ܦܘܣܝܛܝܒ̈ܝܐ ܕ-GIS" ܟܡܥܣܩܝ ܥܠܗ ܕܦܠܛܐ ܠܥܡܪܐ ܘܠܢܣܝܢܐ، "ܐܦ ܐܝܡܢ ܕܫܪܝܪܘܬܐ ܕܡܬܚܙܝܐ ܕܝܠܗ ܟܥܒܕܐ ܠܗ ܚܘܝܐ ܚܝܠܢܐ ܕܡܐܡܪ̈ܐ" (ܬܡܢ). ܘܓܘ ܟܢܘܫܝܐ ܕܨܚܚܐ 8b (ܦܐܬܐ 82) – ܬܚܘܡܐ: ܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ ܛܒ̈ܐ ܝܢܐ ܒܕܘܟܬܐ ܕܝܗܝ̈ܒܬܐ ܠܘܬ ܓܐܘܓܪܦܝܐ، ܘ"ܒܨܝܪ ܡܘܬܪ̈ܢܐ ܝܢܐ ܒܚܘܝܐ ܕܢܣܝܢܐ ܐܝܟܝܐ ܕܐܬܪܐ" – ܨܘܪܬܐ ܕܦܢܝ̈ܬܐ ܣܛܐܛܝܣܛܝܩ̈ܝܬܐ ܟܐܡܪܐ ܐܝܟܐ، ܠܐ ܕܟܝ ܟܡܪܓܫ ܐܢܫܐ ܕܥܡܪ ܬܡܢ. ܐܝܬܝܩܐ ܘܢܡܘܣܐ (Dawson, 2020, pp. 140-146): ܢܛܪܬܐ ܕܕܘܟܬܐ، ܛܝ̈ܣܐ ܕܠܐ ܛܝܣܐ (drones) ܘܨܘܪ̈ܬܐ ܕܣܛܠܝܛ ܒܚܬܝܬܘܬܐ ܪܡܬܐ ܡܥܠܬܐ ܝܢܐ ܓܘ ܓܢܝܙܘܬܐ (privacy) ܕܟܒܥܝܐ ܢܡܘܣܐ ܐܝܬܝܩܝܐ (Dawson ܟܡܚܘܝܐ ܢܡܘܣܐ ܕ-GISCI)؛ ܘܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ ܒܫܘܬܦܘܬܐ (crowdsourced) ܡܨܝ ܕܡܦܠܚܝ ܩܐ ܕܚܝܐ ܠܣܦܪ̈ܐ ܒܐܝܕܐ ܕܐܝܢܐ ܕܐܝܬ ܠܗ ܚܝܠܐ – ܫܘܐܠܐ "ܡܨܐ ܦܘܫܩܐ ܕܡܦܠܚܝ ܒܗ ܡܪ̈ܝ ܨܒܘܬܐ ܩܐ ܚܒܠܐ ܕܚܕܐ ܓܘܕܐ؟" ܟܡܫܬܐܠ ܡܢ ܩܕܡ.
ܠܘܚܐ 5. GIS ܘܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ ܬܫܥܝܬܢ̈ܝܬܐ
| ܡܐܢܐ | ܡܘܕܝ ܟܥܒܕ | ܐܦܣܢܘܬܐ ܘܛܝܡܐ | ܡܨܥܬܐ | ܡܥܝܪ̈ܢܘܬܐ (notes) |
|---|---|---|---|---|
| QGIS | GIS ܕܚܘܫܒܢܐ (desktop) ܓܡܝܪܐ ܘܡܓܢ: ܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ، ܬܘܩܢܐ، ܦܘܫܩܐ ܕܐܬܪܐ، ܬܘܣܦ̈ܬܐ (plugins)، Python. | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܪܡܙܐ | ܢܘܣܚܐ 4.2 (2026)؛ ܢܘܣܚܐ LTR ܩܐ ܦܪܘܝ̈ܩܬܐ ܐܪ̈ܝܟܐ. ܥܒܪܝܐ ܘܦܐܝ̈ܠܐ SHP ܒܥܒܪܝܐ – ܐܝܬ ܥܘܕܪܢܐ، ܓܒ ܙܒ̈ܢܐ ܟܒܥܝ ܬܘܩܢܐ ܕܪܡܙܢܘܬܐ (encoding). |
| ArcGIS Pro / Online | GIS ܬܓܪܝܐ ܕ-Esri: ܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ 2D/3D ܡܩܕܡ̈ܬܐ، ܦܘܫܩܐ (analytics)، ܡܕܒܪܢܘܬܐ ܕܝܗܝ̈ܒܬܐ، ܬܫܡܫ̈ܬܐ ܕܥܢܢܐ (cloud). | ܒܦܪܥܢܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܒܪܐܘܙܪ | ܪܘܒܐ ܕܡܕܪ̈ܫܝܬܐ ܥܠܝ̈ܬܐ ܐܝܬ ܠܗܝ̇ ܐܦܣܢܘܬܐ ܕܩܡܦܘܣ. 21 ܝܘ̈ܡܐ ܕܢܣܝܘܢܐ. |
| GeoDa | ܦܘܫܩܐ ܡܒܨܝܢܐ (exploratory) ܕܝܗܝ̈ܒܬܐ ܕܐܬܪܐ: ܡܚܘ̈ܝܢܐ ܕ-Moran، ܥܢܩܘ̈ܕܐ (clusters) ܕܐܬܪܐ، ܪܝܓܪܫܢ (regression) ܕܐܬܪܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ | ܢܘܣܚܐ 1.22 (2025). Luc Anselin، Chicago. ܡܐܢܐ ܕܡܢܗ ܡܨܝܚ ܕܝܠܦܚ ܣܛܐܛܝܣܛܝܩܐ ܕܐܬܪܐ. |
| Leaflet | ܟܬܒܘܬܐ ܕܪܡܙܐ ܕ-JavaScript ܩܠܝܠܬܐ ܩܐ ܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ interactive ܓܘ ܣܐܝܛ. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܫܬܐܣܐ ܕܪܘܒܐ ܕܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ ܕܐܢܛܪܢܝܬ ܠܐ ܬܓܪ̈ܝܬܐ. ܢܘܣܚܐ 1.9؛ 2.0 ܓܘ beta. |
| kepler.gl | visualization ܕܝܗܝ̈ܒܬܐ ܓܐܘܓܪܦ̈ܝܬܐ ܪ̈ܒܬܐ ܓܘ ܒܪܐܘܙܪ (WebGL)، ܕܠܐ ܪܡܙܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ / ܪܡܙܐ | ܝܗܝ̈ܒܬܐ ܟܦܝܫܝ ܓܘ ܒܪܐܘܙܪ – ܠܐ ܟܣܠܩܝ ܠܣܝܪܒܪ. OpenJS Foundation. |
| Google Earth Engine | ܦܘܠܚܢܐ ܕܨܘܪ̈ܬܐ ܕܣܛܠܝܛ ܘܝܗܝ̈ܒܬܐ ܓܐܘ-ܕܐܬܪܐ ܒܡܫܘܚܬܐ ܕܥܠܡܐ ܟܠܗ، ܓܘ ܥܢܢܐ (cloud). | ܡܓܢ ܩܐ ܡܕܪ̈ܫܝܬܐ | ܒܪܐܘܙܪ / ܪܡܙܐ | ܡܓܢ ܩܐ ܒܘܨܝܐ ܘܩܐ ܡܦܠܚܢܘܬܐ ܠܐ ܬܓܪܝܬܐ؛ ܟܒܥܐ ܟܬܝܒܬܐ ܕܦܪܘܝܩܬ. ܩܐ ܫܘܐ̈ܠܐ ܕܡܦܠܚܢܘܬܐ ܕܐܪܥܐ، ܩܘܪܒܐ ܕܒܢܝܢܐ، ܝܘܪܩܐ ܕܡܕܝܢܬܐ. |
| StoryMap JS | ܬܫܥܝܬܐ ܣܡܝܟܬܐ ܥܠ ܨܘܪܬܐ ܕܐܬܪܐ: ܕܘܟ̈ܝܬܐ ܥܠ ܨܘܪܬܐ ܥܡ ܡ̈ܠܐ ܘ-media (Knight Lab). | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ | ܟܬܝܒܬܐ ܟܒܥܝܐ ܚܘܫܒܢܐ (account) ܕ-Google؛ ܨܘܪ̈ܬܐ ܢܛܝܪ̈ܬܐ ܝܢܐ ܓܘ ܕܘܟܬܐ ܐܚܪܬܐ. ܩܐ ܡܦܪܣܡܢܘܬܐ ܘܩܐ ܝܘܠܦܢܐ، ܠܐ ܩܐ ܦܘܫܩܐ. |
| Map Warper | Georeferencing ܕܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ ܬܫܥܝܬܢ̈ܝܬܐ: ܟܣܝܡܚ ܨܘܪܬܐ ܕܣܩܝܢܬܐ ܥܠ ܨܘܪܬܐ ܕܐܕܝܘܡ ܘܟܡܦܩܚ (export). | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ | ܣܝܪܒܪ ܕܡܬܛܘܥ̈ܢܐ ܥܡ ܡܘܗܒ̈ܬܐ – ܐܝܬܘܬܐ ܠܐ ܝܠܗ̇ ܡܫܪܪܬܐ. ܪܡܙܐ ܓܘ GitHub ܩܐ ܬܘܩܢܐ ܕܝܠܘܟܘܢ. |
| GovMap | ܬܪܥܐ ܐܘܡܬܢܝܐ ܕܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ ܕܐܝܣܪܐܝܠ: ܡܘܢ̈ܥܐ، ܦܠ̈ܓܐ ܕܐܪܥܐ (parcels)، ܬܚܬܝ̈ܬܐ ܕܡ̈ܠܐ، ܬܚܬܝ̈ܬܐ ܝܚܝܕ̈ܝܬܐ. | ܡܓܢ (ܩܦܝܠܐ) | ܒܪܐܘܙܪ | ܡܨܥܬܐ (interface) ܒܥܒܪܝܐ. ܡܢܬܐ ܡܢ ܬܚܬܝ̈ܬܐ ܘ-API ܟܒܥܝ ܟܬܝܒܬܐ ܕܫܡܐ. |
| CBS – ܬܚܬܝ̈ܬܐ ܓܐܘܓܪܦ̈ܝܬܐ | ܬܚܬܝܬܐ ܕܦܢܝ̈ܬܐ ܣܛܐܛܝܣܛܝܩ̈ܝܬܐ (GIS) ܩܐ ܡܚܬܬܐ ܥܡ ܝܗܝ̈ܒܬܐ ܕܥܡܐ (demographic)، ܘܟܬܒ̈ܐ ܕܦܘܫܩܐ. | ܡܓܢ (ܩܦܝܠܐ) | ܒܪܐܘܙܪ | ܚܕܝܘܬܐ ܕܐܬܪܐ ܕܝܗܝ̈ܒܬܐ ܕܡܢܝܢܐ ܕܥܡܐ (census). ܬܚܬܝܬܐ ܕ-2008 ܐܦ ܓܘ data.gov.il. ܚܘܕ̈ܬܐ – ܓܘ ܦܐܬܐ GIS ܕ-CBS. |
ܡܥܝܪܢܘܬܐ. ܣܐܝܛ ܕ-CBS ܓܒ ܙܒ̈ܢܐ ܟܡܢܥ ܡܛܝܬܐ ܒܚܘܕܝܗ؛ ܐܣܘܪܐ (link) ܡܫܪܪܐ ܝܠܗ ܒܐܝܕܐ. ܬܚܬܝܬܐ ܕܦܢܝ̈ܬܐ ܣܛܐܛܝܣܛܝܩ̈ܝܬܐ ܕܡܦܪܣܡܬܐ ܝܠܗ̇ ܓܘ ܦܐܬܐ ܕ-2011 ܝܠܗ̇؛ ܬܚܬܝ̈ܬܐ ܚܕ̈ܬܐ ܝܬܝܪ – ܓܘ ܦܐܬܐ GIS ܕ-CBS.
6. ܡܘܕܝ̈ܠܐ ܣܡܝܟ̈ܐ ܥܠ ܥܒܘ̈ܕܐ (agent-based) ܘ-simulation ܟܢܫܝܐ
ܥܒܕܐ ܕܡܘܕܝ̈ܠܐ ܣܡܝܟ̈ܐ ܥܠ ܥܒܘ̈ܕܐ (agent-based modeling) ܟܗܦܟ ܐܘܪܚܐ ܕܒܘܨܝܐ: ܒܕܘܟܬܐ ܕܫܘܠܡܐ ܕܢܡܘܣܐ ܡܢ ܝܗܝ̈ܒܬܐ، ܟܡܚܕܕܚ ܢܡܘ̈ܣܐ ܦܫܝ̈ܛܐ ܩܐ ܥܒܘ̈ܕܐ (agents) ܘܟܒܚܪܚ ܐܝܢܐ ܓܠܝܢܐ ܟܢܫܝܐ ܪܒܐ (macro) ܟܪܒܐ ܡܢܝܗܝ – ܦܘܪܫܐ ܓܘ ܡܕܝܢܬܐ ܡܢ ܨܒܝܢ̈ܐ ܩܠܝܠ̈ܐ (Schelling)، ܫܠܡܘܬܐ ܡܢ ܡܥܒܕܢܘܬܐ ܕܚܕ̈ܕܐ، ܥܝܕܐ ܡܢ ܫܘܬܦܘܬܐ ܡܬܢܝܬܐ. ܐܗܐ ܡܐܢܐ ܝܠܗ ܩܐ ܬܐܘܪܝܐ ܝܬܝܪ ܡܢ ܩܐ ܢܣܝܢܐ (empirical)، ܘܡܛܠ ܗܕܐ ܚܫܝܚܐ ܝܠܗ ܚܬܝܬܐܝܬ ܩܐ ܒܨܘܝܐ ܕܒܥܐ ܕܒܚܪ ܐܢ ܦܘܫܩܐ ܕܝܠܗ ܡܢ ܟܠ ܥܠܡ ܡܨܐ ܕܒܢܐ ܓܠܝܢܐ.
NetLogo ܝܠܗ̇ ܬܪܥܐ ܕܡܥܠܬܐ ܕܠܐ ܬܟܬܘܫܐ – "ܬܚܘܡܐ ܢܚܝܬܐ، ܬܛܠܝܠܐ ܪܡܐ" – ܥܡ ܒܝܬ ܟܬܒ̈ܐ ܕܡܘܕܝ̈ܠܐ ܩܠܐܣܝܩ̈ܝܐ ܒܢܝܐ ܓܘܗ̇. ܐܝܢܐ ܕܟܟܬܒ Python ܒܕ ܐܙܠ ܠ-Mesa؛ ܡܘܕܝ̈ܠܐ ܥܡ GIS – GAMA. ܒܝܬ ܟܬܒ̈ܐ ܕܡܘܕܝ̈ܠܐ ܕ-CoMSES ܝܠܗ ܕܘܟܬܐ ܕܒܨܝܐ ܕܡܘܕܝܠ ܕܐܝܬ ܩܕܡ ܕܟܬܒܚ ܚܕ ܚܕܬܐ.
ܫܪܫܐ ܩܕܡ ܡܐܢܐ. Dawson (2020، ܦܐ̈ܬܐ 4-9) ܟܚܬܬܐ ܡ̈ܠܐ: ܡܘܕܝܠ (model) ܟܡܚܘܐ، simulation ܟܡܦܠܚ ܒܡܘܕܝܠ – ܘܐܘܪܚܐ ܟܒܢܝܐ "ܡܢ ܬܚܬ ܠܥܠ، ܡܢ ܙܥܘܪܐ ܠܪܒܐ"، ܗܕܟܐ ܕܛܘ̈ܦܣܐ ܟܪܒܝ ܡܢ ܥܒܕܐ ܕܚܕ̈ܕܐ ܕܥܒܘ̈ܕܐ. ܬܪܝܢ ܫܘܐ̈ܠܐ ܕܝܠܗ̇ ܟܒܥܝ ܦܘܢܝܐ ܓܘ ܨܚܚܐ ܕܐܘܪܚܐ: "ܡܘܕܝ̈ܠܐ ܟܡܚܘܝ ܥܠܡܐ، ܝܢ ܦܘܫܩܐ ܕܒܨܘܝܐ ܕܥܠܡܐ؟" ܘܕܟܝ ܟܡܫܪܪܚ – verification (ܡܘܕܝܠ ܟܦܠܚ ܫܦܝܪ) ܩܘܒܠ validation (ܡܘܕܝܠ ܫܪܝܪܐ ܒܢܝܐ ܝܠܗ). Cioffi-Revilla (2017، ܦܐ̈ܬܐ 384-390) ܟܦܪܫ ܐܗܐ ܠܕܪ̈ܓܐ: ܫܘܐ̈ܠܐ ܕܒܘܨܝܐ ܩܕܡ ܟܠ ܡܕܡ ܝܢܐ ܘܟܦܣܩܝ ܕܪܓܐ ܕܫܪܝܪܘܬܐ (fidelity) ܕܡܘܕܝܠ – ܡܢ ܦܫܝܛܘܬܐ ܬܐܘܪܝܬܐ ܗܠ ܬܘܪܨܐ (calibration) ܢܣܝܢܝܐ ܓܡܝܪܐ (ܦܐܬܐ 385) – ܘܣܒܠܬܐ ܕܫܪܝܪܘܬܐ "ܡܢ ܟܠ ܥܠܡ ܠܐ ܝܠܗ̇ ܐܣܝܪܬܐ" ܥܡ ܛܝܡܐ ܝܕܥܢܝܐ ܕܡܘܕܝܠ (ܦܐ̈ܬܐ 382-383)؛ verification ܐܝܟ ܬܪܝܨܘܬܐ (validity) ܓܘܝܬܐ ܝܠܗ – "ܡܘܕܝܠ ܕܠܐ ܡܫܪܪܐ ܝܠܗ ܠܐ ܦܐܝܐ ܝܠܗ ܩܐ ܦܘܫܩܐ" – ܘܟܡܬܥܒܕ ܒܩܪܝܢܐ ܕܪܡܙܐ ܣܕܪܐ-ܣܕܪܐ، ܒ-profile ܕܣܓܝܐܘܬܐ (frequency) ܕܩܪ̈ܝܢܐ ܠ-functions ܘܒܒܘܨܝܐ ܕܦܪ̈ܡܝܛܪܐ (parameter sweep) ܕܟܓܠܐ ܠܐ ܥܡܝ̈ܘܬܐ (ܦܐ̈ܬܐ 388-389)؛ validation ܦܐܝܘܬܐ ܕܛܘ̈ܦܣܐ ܝܠܗ̇ ܒܝܢܝ ܡܦܩܢܐ (output) ܕ-simulation ܘܝܗܝ̈ܒܬܐ ܢܣܝܢ̈ܝܬܐ – ܗܝܣܛܘܓܪ̈ܡܐ، moments، ܣܕܪ̈ܐ ܕܙܒܢܐ، ܡܚܘ̈ܝܢܐ ܐܝܟ Gini – ܘ"ܟܠ ܐܡܢ ܐܣܝܪܐ ܝܠܗ ܒܦܐܝܘܬܐ ܕܝܗܝ̈ܒܬܐ ܕ-simulation ܥܡ ܝܗܝ̈ܒܬܐ ܢܣܝܢ̈ܝܬܐ" (ܦܐ̈ܬܐ 389-390). ܘܬܪܝܢ ܙܘܗܪ̈ܐ: "ܪܡܙܐ ܕ-simulation ܟܡܬܚܒܠ ܒܣܓܝ، ܝܬܝܪ ܒܣܓܝ ܡܢ ܡܘܕܝ̈ܠܐ ܡܬܡܛܝܩ̈ܝܐ ܝܢ ܣܛܐܛܝܣܛܝܩ̈ܝܐ" – simulations ܝܕ̈ܝܥܐ ܐܒܝܕ̈ܐ ܗܘܘ ܙܒܢܐ ܟܪܝܐ ܒܬܪ ܕܟܬܝܒ̈ܐ ܗܘܘ، ܘܦܝܫܠܗ ܡܢܝܗܝ ܒܣ ܡܘܕܝܠ ܕܚܘܫܒܐ (ܦܐܬܐ 388)؛ ܘ-verification ܘ-validation "ܒܢܦܫܝܗܘܢ ܠܐ ܣܦܩܝ" ܩܐ ܕܝܢܐ ܕܐܝܟܝܘܬܐ – ܓܢܒܝܗܘܢ ܐܝܬ ܬܠܬܐ ܡܫܘ̈ܚܬܐ ܕ-Lave ܘ-March (1993، ܐܝܟ ܕܡܬܝ̈ܬܐ ܝܢܐ ܓܘ Cioffi-Revilla): ܫܪܪܐ، ܫܘܦܪܐ (ܚܣܝܟܘܬܐ (parsimony) ܘܐܣܟܝܡܐ) ܘܟܐܢܘܬܐ – ܬܘܣܦܬܐ ܕܡܘܕܝܠ ܠܥܠܡܐ ܛܒܐ ܝܬܝܪ (ܦܐ̈ܬܐ 391-393). ܩܕܡ ܕܓܒܚ ܡܐܢܐ: Abar ܘܐܚܪ̈ܢܐ (2017, as cited in Dawson) ܟܬܚܘܝ 85 ܨܪ̈ܪܐ ܕ-ABM – NetLogo ܬܪܥܐ ܕܡܥܠܬܐ ܝܠܗ̇، ܠܐ ܝܚܝܕܝܬܐ. ܐܝܬܝܩܐ ܘܢܡܘܣܐ (ܬܡܢ): ܡܘܕܝܠ ܡܨܐ ܕܥܒܕ ܚܒܠܐ – ܐܝܡܢ ܕܟܪܫܡܚ ܦܪ̈ܨܘܦܐ ܩܐ ܥܒܕܐ ܥܠ ܫܬܐܣܐ ܕܡܢܒܝܢܘܬܐ (prediction)، ܐܝܡܢ ܕܡܢܒܝܢܘܬܐ ܣܡܝܟܬܐ ܝܠܗ̇ ܥܠ ܥܘܒܕܐ ܥܒܝܪܐ ܕܫܚܠܦܠܗ، ܘܐܝܡܢ ܕܠܝܬ ܐܘܪܚܐ ܕܬܘܪܨܐ ܕܝܗܝ̈ܒܬܐ ܕܡܥܠܬܐ؛ ܘܐܢ ܝܗܝ̈ܒܬܐ ܡܢ ܟܠ ܥܠܡ ܝܗܝ̈ܒܐ ܗܘܘ ܩܐ ܢܝܫܐ ܕܡܘܕܝܠ.
ܠܘܚܐ 6. ܡܘܕܝ̈ܠܐ ܣܡܝܟ̈ܐ ܥܠ ܥܒܘ̈ܕܐ ܘ-simulation ܟܢܫܝܐ
| ܡܐܢܐ | ܡܘܕܝ ܟܥܒܕ | ܐܦܣܢܘܬܐ ܘܛܝܡܐ | ܡܨܥܬܐ | ܡܥܝܪ̈ܢܘܬܐ (notes) |
|---|---|---|---|---|
| NetLogo | ܕܘܟܬܐ ܕ-ABM ܕܡܬܚܙܝܐ ܝܬܝܪ ܡܢ ܟܠ: ܠܫܢܐ ܦܫܝܛܐ، ܡܨܥܬܐ ܓܪܦܝܬܐ، ܒܝܬ ܟܬܒ̈ܐ ܕܡܘܕܝ̈ܠܐ، ܢܘܣܚܐ ܕܒܪܐܘܙܪ. | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܒܪܐܘܙܪ | ܢܘܣܚܐ 7.0 (2026). ܕܘܟܬܐ ܕܫܘܪܝܐ؛ ܟܬܒܐ ܕܝܘܠܦܢܐ: Wilensky & Rand. |
| Mesa | ܛܘܦܣܐ ܕ-ABM ܓܘ Python ܥܡ visualization ܓܘ ܒܪܐܘܙܪ (Solara). | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܢܘܣܚܐ 3.5 (2026). ܩܐ ܐܝܢܐ ܕܡܢ ܩܕܡ ܟܦܠܚ ܓܘ Python ܘܒܥܐ ܕܐܣܪ ܡܘܕܝܠ ܠ-pandas ܘ-scikit-learn. |
| Repast | ܨܪܪܐ ܥܬܝܩܐ ܕ-ABM: Simphony (Java)، HPC (C++) ܘ-Repast4Py (Python) ܩܐ simulations ܪ̈ܒܬܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܪܡܙܐ | Argonne National Laboratory. ܩܐ ܦܪܘܝ̈ܩܬܐ ܝܩܘܪ̈ܐ؛ ܣܪܛܐ ܕܝܘܠܦܢܐ ܚܪܝܦܐ ܝܬܝܪ ܡܢ NetLogo. |
| GAMA Platform | ܕܘܟܬܐ ܕܡܘܕܝ̈ܠܐ ܩܐ simulations ܕܐܬܪܐ ܥܡ GIS ܒܢܝܐ ܓܘܗ̇، ܒܠܫܢܐ GAML. | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܪܡܙܐ | ܢܘܣܚܐ 2025.06. ܓܘܒܝܐ ܐܝܡܢ ܕܡܘܕܝܠ ܣܢܝܩ ܝܠܗ ܠܨܘܪܬܐ ܕܐܬܪܐ ܫܪܝܪܬܐ – ܡܕܝܢܬܐ، ܦܢܝܬܐ، ܙܘܥܐ. |
| MASON | ܟܬܒܘܬܐ ܕ-simulation ܡܣܪܗܒܬܐ ܓܘ Java ܥܡ visualization 2D/3D ܒܨܒܝܢܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܡܘܢܥܐ ܥܬܝܩܐ (cs.gmu.edu/~eclab) ܟܡܫܕܪ ܠܦܐܬܐ ܕܡܢܬܐ ܕܝܘܠܦܢܐ – ܡܦܠܚܘܢ ܒܐܗܐ ܐܣܘܪܐ (link). ܢܘܣܚܐ 22. |
| Agents.jl | ܛܘܦܣܐ ܕ-ABM ܒܥܒܕܐ ܪܡܐ ܓܘ Julia، ܥܡ ܓܪܦܝܩܐ ܕ-Makie. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܢܘܣܚܐ 7.0 (2026). ܩܐ ܡܘܕܝ̈ܠܐ ܪ̈ܒܐ ܕܓܘܝܗܝ Python ܡܬܝܢܐ ܝܠܗ ܒܣܓܝ. |
| AnyLogic | simulation ܕܣܓܝ ܐܘܪ̈ܚܬܐ ܬܓܪܝܬܐ: ܥܒܘ̈ܕܐ (agents)، ܓܕ̈ܫܐ ܦܪ̈ܝܫܐ (discrete events) ܘ-system dynamics ܓܘ ܚܕ ܡܘܕܝܠ. | ܡܓܢ + ܒܦܪܥܢܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ | ܢܘܣܚܐ Personal Learning ܡܓܢ (ܗܠ 10 ܙܢ̈ܐ ܕܥܒܘ̈ܕܐ)؛ ܐܦܣܢܘܬܐ ܕܒܘܨܝܐ ܕܡܕܪܫܬܐ ܥܠܝܬܐ – ܒܦܪܥܢܐ، ܩܐ ܡܕܪ̈ܫܝܬܐ. |
| CoMSES Net / OpenABM | ܒܝܬ ܟܬܒ̈ܐ ܦܬܝܚܐ ܕܡܘܕܝ̈ܠܐ ܕܡܒܘܚܪ̈ܐ ܝܢܐ ܒܝܕ ܚܒܪ̈ܐ (peer-reviewed) ܩܐ ܥܒܕܐ ܕܡܘܕܝ̈ܠܐ ܚܘܫܒܢܝ̈ܐ ܟܢܫ̈ܝܐ-ܐܝܩܘܠܘܓ̈ܝܐ، ܘܟܢܘܫܝܐ (community). | ܡܓܢ (ܩܦܝܠܐ) | ܒܪܐܘܙܪ | ܡܘܕܝ̈ܠܐ ܟܩܒܠܝ DOI. ܒܨܘܢ ܠܐܟܐ ܩܕܡ ܕܟܬܒܝܬܘܢ؛ ܦܪܣܡܘܢ ܠܐܟܐ ܐܝܡܢ ܕܫܠܡܝܬܘܢ. |
| Vensim | System dynamics: ܐܘܨܪ̈ܐ (stocks)، ܪ̈ܕܝܐ (flows) ܘܚܘܕ̈ܪܐ ܕ-feedback (Ventana Systems). | ܡܓܢ + ܒܦܪܥܢܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ | Vensim PLE ܡܓܢ ܩܐ ܡܕܪ̈ܫܝܬܐ ܘܩܐ ܡܦܠܚܢܘܬܐ ܝܚܝܕܝܬܐ. ܐܘܪܚܐ ܕܡܫܠܡܐ ܠ-ABM – ܛܟܣܐ ܒܕܪܓܐ ܕ-macro. |
ܡܥܝܪܢܘܬܐ. NetLogo ܥܒܪܠܗ̇ ܠܕܘܡܝܢ netlogo.org (ܡܘܢܥܐ ܥܬܝܩܐ ܓܘ northwestern ܟܡܫܕܪ ܠܬܡܢ). Vensim ܘ-AnyLogic ܡܐܢ̈ܐ ܕ-system dynamics ܘ-simulation ܕܣܓܝ ܐܘܪ̈ܚܬܐ ܝܢܐ، ܠܐ ABM ܕܟܝܐ.
7. ܟܢܫܐ ܕܝܗܝ̈ܒܬܐ ܕܝܓܝܛܠܝ̈ܬܐ
ܬܪܬܝܢ ܫܪ̈ܒܬܐ: ܒܘܨܝܐ ܕܫܘܐ̈ܠܐ (survey) ܓܘ ܫܒܝܟܬܐ – ܡܐܢܐ ܥܬܝܩܐ ܕܩܒܠܠܗ ܡܨܥܬܐ ܚܕܬܐ – ܘܟܢܫܐ ܕ"ܥܩ̈ܒܬܐ ܕܝܓܝܛܠܝ̈ܐ" (digital traces; Salganik, 2018): scraping ܕܣܐܝ̈ܛܐ، ܡܛܝܬܐ ܠ-API ܕܐܬܪ̈ܘܬܐ (platforms)، ܘܐܚܕܐ ܕܡ̈ܠܐ ܡܢ ܡܨܝ̈ܕܬܐ ܟܢܫ̈ܝܬܐ. ܩܕܡܝܬܐ ܟܡܩܝܡܐ ܫܘܐܠܐ ܕܪܡܙܢܘܬܐ ܘܬܪܝܨܘܬܐ (validity)؛ ܬܪܝܢܝܬܐ ܟܡܩܝܡܐ، ܩܕܡ ܟܠ ܡܕܡ، ܫܘܐܠܐ ܕܐܝܬܝܩܐ ܘܢܡܘܣܐ – ܫܪ̈ܛܐ ܕܡܦܠܚܢܘܬܐ (Terms of use) ܕܐܬܪܐ، ܓܢܝܙܘܬܐ (privacy) ܕܡܦܠܚܢ̈ܐ، ܘܫܘܪܪܐ ܕܓܘܕܐ ܕܐܝܬܝܩܐ. Salganik (2018، ܨܚܚܐ 6، ܦܐ̈ܬܐ 281-354) ܝܠܗ ܩܪܝܢܐ ܕܣܢܝܩ ܝܠܗ.
ܩܐ ܒܘܨܝܐ ܕܫܘܐ̈ܠܐ ܓܘ ܐܝܣܪܐܝܠ – ܪܘܒܐ ܕܡܕܪ̈ܫܝܬܐ ܥܠܝ̈ܬܐ ܐܝܬ ܠܗܝ̇ ܐܦܣܢܘܬܐ Qualtrics؛ LimeSurvey ܝܠܗ ܚܠܦܐ ܦܬܝܚܐ ܐܝܡܢ ܕܠܝܬ. ܡܦܩܢܐ (output) ܕܟܠܗܘܢ – ܦܐܝܠ ܐܩܣܠ ܓܘ ܛܘܦܣܐ ܬܩܝܢܐ (the standard data template) ܕܣܐܝܛ، ܝܢ ܦܐܝܠ SPSS ܕܦܐܬܐ ܡܢ SPSS ܠܐܩܣܠ ܟܫܚܠܦ.
ܫܪܫܐ ܩܕܡ ܡܐܢܐ. Salganik (2018، ܦܐ̈ܬܐ 17-41) ܟܡܢܐ ܥܣܪܐ ܕܝܠܝ̈ܬܐ ܕܡܒܘ̈ܥܐ ܕܝܗܝ̈ܒܬܐ ܪ̈ܒܬܐ (big data)، ܘܟܟܢܫ ܠܗܝ̇ ܒܓܣܘܬܐ: ܬܠܬܐ "ܡܘܬܪ̈ܢܐ ܪܘܒܐ ܕܙܒ̈ܢܐ" – ܪ̈ܒܐ، ܦܥܠ̈ܐ ܟܠ ܐܡܢ (always-on)، ܠܐ ܡܦܢ̈ܝܐ (ܡܫܘܚܬܐ ܠܐ ܟܫܚܠܦܐ ܥܘܒܕܐ) – ܘܫܒܥܐ "ܥܣܝ̈ܩܐ ܪܘܒܐ ܕܙܒ̈ܢܐ": ܠܐ ܓܡܝܪ̈ܐ ("ܠܐ ܦܪܫ ܟܡܐ ܪ̈ܒܬܐ ܝܢܐ ܝܗܝ̈ܒܬܐ، ܒܠܟܝ ܠܝܬ ܓܘܝܗܝ ܝܕܥܬܐ ܕܒܥܝܬܘܢ")، ܠܐ ܡܬܡܛܝ̈ܢܐ، ܠܐ ܕܡܝ̈ܐ ܠܟܢܫܐ ܟܠܢܝܐ (non-representative؛ "ܒܝܫ̈ܐ ܩܐ ܦܘܫܛܐ ܠܒܪ ܡܢ ܕܘܡܝܐ، ܐܠܐ ܡܘܬܪ̈ܢܐ ܩܐ ܦܘܚܡ̈ܐ ܓܘ ܕܘܡܝܐ"، ܦܐܬܐ 29)، ܕܙܝܥܝ (drifting؛ ܙܘܥܐ ܓܘ ܟܢܫܐ، ܓܘ ܡܦܠܚܢܘܬܐ ܘܓܘ ܛܟܣܐ ܟܥܣܩ ܨܠܝ̈ܢܐ ܕܙܒܢܐ ܐܪܝܟܐ)، ܡܚܠܛ̈ܐ ܒܝܕ ܐܠܓܘܪܝܬܡ̈ܐ ("ܥܘܒܕܐ ܓܘ ܛܟܣ̈ܐ ܕܝܗܝ̈ܒܬܐ ܪ̈ܒܬܐ ܠܐ ܝܠܗ ܛܒܝܥܝܐ؛ ܐܗܘ ܡܬܕܒܪܐ ܝܠܗ ܒܝܕ ܢܝܫ̈ܐ ܕܗܢܕܣܐ ܕܛܟܣ̈ܐ"، ܦܐܬܐ 35)، ܛܢܦ̈ܐ ("ܡܠܝ̈ܐ ܕܩܛܡܐ ܘ-spam"، ܦܐܬܐ 37) ܘܪܓܝܫ̈ܐ. ܘܢܡܘܣܐ ܥܠܝܐ: "ܛܘ̈ܦܣܐ ܕܝܗܝ̈ܒܬܐ ܪ̈ܒܐ ܐܘܪܚܐ ܝܢܐ ܠܢܝܫܐ، ܠܐ ܢܝܫܐ ܒܢܦܫܗ" (ܦܐܬܐ 17). ܘܥܠ ܒܘܨܝܐ ܕܫܘܐ̈ܠܐ: "ܟܠ ܐܡܢ ܒܕ ܣܢܝܩܚ ܗܘܝܚ ܕܫܐܠܚ ܫܘܐ̈ܠܐ ܠܐܢܫ̈ܐ" – ܐܝܟܢܝ̈ܘܬܐ ܓܘܝ̈ܬܐ ܐܝܟ ܪܓܫܐ، ܝܕܥܬܐ ܘܣܟܝܘܬܐ ܠܐ ܐܝܬܠܗܝܢ ܓܘ ܝܗܝ̈ܒܬܐ ܕܥܘܒܕܐ، ܐܦ ܓܡܝܪ̈ܬܐ (ܦܐ̈ܬܐ 87-88)؛ ܘܓܘܒܝܐ ܕܕܘܡܝܐ ܕܡܣܬܒܪܢܘܬܐ (probability) ܥܣܩܐ ܟܗܘܐ ܒܫܪܪܐ ܐܝܡܢ ܕܓܘܒܝܐ ܕܠܐ ܡܣܬܒܪܢܘܬܐ ܟܦܬܚ ܡܨܝܐܘ̈ܬܐ ܚܕ̈ܬܐ – ܐܢ ܟܬܪܨܚ (ܦܐܬܐ 99). ܩܐ ܡܨܝ̈ܕܬܐ ܟܢܫ̈ܝܬܐ (Dawson, 2020, pp. 349-355): ܝܗܝ̈ܒܬܐ "ܠܐ ܒܥܝ̈ܬܐ ܘܠܐ ܟܬܝ̈ܒܬܐ ܡܢ ܩܕܡ، ܘܪܘܒܐ ܕܙܒ̈ܢܐ ܕܣܓܝ ܐܣܟܝ̈ܡܐ ܝܢܐ" (Brooker et al., 2016, as cited in Dawson) – ܡ̈ܠܐ، ܐܣܘܪܐ (link)، ܨܘܪܬܐ، ܒܝܕܝܘ – ܘܡܛܠ ܗܕܐ ܐܘܪܚܐ ܕܦܘܫܩܐ (ܦܘܫܩܐ ܕܬܚܘܡܐ ܕܡ̈ܠܐ (content)، ܕܡܡܠܠܐ (discourse)، ܕܪܓܫܐ (sentiment)، ܕܡܨܝܕܬܐ، ܕܙܒܢܐ) ܓܒܝܐ ܝܠܗ ܠܦܘܬ ܫܘܐܠܐ، ܠܐ ܠܦܘܬ ܡܐ ܕܡܐܢܐ ܟܛܒܥ؛ ܘܡܕܒܪܢܘܬܐ ܕ-API ܕܐܬܪ̈ܘܬܐ "ܟܐܙܠܐ ܘܟܡܟܪܝܐ"، ܗܕܟܐ ܕܝܗܝ̈ܒܬܐ ܕܩܒܝܠ̈ܐ ܝܢܐ ܒܝܕܗ̇ "ܠܐ ܡܨܝܚ ܕܡܬܥܒܕ̈ܢ ܬܘܒ ܚܬܝܬܐܝܬ ܡܛܠ ܗܘܢܐ ܠܐ ܝܕܝܥܐ ܕܐܠܓܘܪܝܬܡ ܕܒܢܐ ܠܗܝ̇" (Felt, 2016, as cited in Dawson) – ܬܚܘܡܐ ܕܟܟܬܒܚ ܓܠܝܐܝܬ. ܩܐ ܒܘܨܝܐ ܕܫܘܐ̈ܠܐ ܓܘ ܫܒܝܟܬܐ (ܦܐ̈ܬܐ 288-294): ܐܣܘܪܐ (link) ܝܚܝܕܝܐ ܩܐ ܟܠ ܡܦܢܝܢܐ ܟܡܢܥ ܡܠܝܐ ܥܦܝܦܐ ܘܟܡܫܒܩ ܡܥܗܕ̈ܢܘܬܐ؛ ܩܐ ܡ̈ܠܐ ܪܓܝܫ̈ܐ – ܫܘܐܠܐ ܠܐ ܬܪܝܨܐ ("ܕܟܝ ܐܢܫ̈ܐ ܐܚܪ̈ܢܐ ܦܢܝ ܗܘܘ") ܓܒ ܙܒ̈ܢܐ ܛܒ ܝܠܗ ܡܢ ܬܪܝܨܐ. ܩܐ webometrics (ܦܐ̈ܬܐ 398-403): "ܟܣܝܘܬܐ ܕܫܒܝܟܬܐ ܡܢܬܢܝܬܐ ܝܠܗ̇" ܘܡܨܠܝܬܐ ܝܠܗ̇ ܠܛܒܬܐ ܕܡܬ̈ܘܬܐ ܕܩܒܠܠܗܝ̇ ܩܕܡ (Thelwall, 2008, as cited in Dawson)، ܘܡܫܩܠ̈ܢܐ ܕܒܨܝܐ (search engines) ܒܢܘ̈ܣܚܐ ܕܡܬ̈ܘܬܐ ܟܓܒܝ ܣܐܝ̈ܛܐ ܐܬܪ̈ܢܝܐ. ܐܝܬܝܩܐ ܘܢܡܘܣܐ: "ܡܦܪܣܡܢܘܬܐ ܓܘ ܫܒܝܟܬܐ ܝܗܝܒܬܐ ܕܥܡܐ ܝܠܗ̇ ܝܢ ܝܚܝܕܝܬܐ؟"؛ ܫܠܡܘܬܐ ܡܢ ܝܕܥܬܐ (informed consent) ܐܝܡܢ ܕܡܫܬܘܬܦ̈ܢܐ ܠܐ ܝܕܥܝ ܕܐܢܝ ܓܘ ܒܘܨܝܐ ܝܢܐ؛ ܠܐ ܝܕܝܥܘܬܐ (anonymity) ܐܝܡܢ ܕܐܬܪܐ ܟܒܥܐ ܫܡܐ ܕܟܬܘܒܐ (ܦܐ̈ܬܐ 349-355)؛ ܡܘܢܥܐ ܕ-IP، ܫܡܐ ܕܡܦܠܚܢܐ ܘܡܒܘܥܐ ܕܫܕܪܬܐ (referrer) ܓܘ ܦܐܝ̈ܠܐ ܕ-log "ܝܗܝ̈ܒܬܐ ܝܚܝܕ̈ܝܬܐ" ܝܢܐ ܠܦܘܬ GDPR، ܘܢܛܪܬܐ ܕܝܠܗܝܢ ܟܒܥܝܐ ܫܠܡܘܬܐ ܩܐ ܢܝܫܐ ܡܚܕܕܐ، ܢܛܘܪܘܬܐ ܘܫܩܠܬܐ ܐܝܡܢ ܕܠܐ ܣܢܝܩ ܝܠܗ ܬܘܒ (ܦܐ̈ܬܐ 188-193) – ܘܓܘ ܐܝܣܪܐܝܠ، ܢܡܘܣܐ ܕܢܛܪܬܐ ܕܓܢܝܙܘܬܐ (Privacy Protection Law) ܘܬܘܪ̈ܨܐ ܕܝܠܗ (ܡܘܕܝ ܢܡܘܣܐ ܟܒܥܐ ܡܢ ܒܨܘܝܐ ܕܟܟܢܫ ܝܕܥܬܐ ܝܚܝܕܝܬܐ، ܒܬܪ ܬܘܪܨܐ 13 – ܓܘ ܦܐܬܐ ܐܝܬܝܩܐ ܕܒܘܨܝܐ، ܦܣܩܐ 11). Drucker ܘ-Albrezzi (2026، ܦܐܬܐ 49) ܟܡܘܣܦܝ ܩܐ ܙܒܢܐ ܕܝܗܝ̈ܒܬܐ ܪ̈ܒܬܐ: "ܥܒܕܐ ܕܝܗܝ̈ܒܬܐ ܐܝܬܠܗܝܢ ܠܐ ܟܐܡܪ ܕܫܠܝܛܐ ܝܠܗ ܐܝܬܝܩܐܝܬ ܕܡܦܠܚܚ ܒܝܗܝ ܕܠܐ ܐܘܪ̈ܚܬܐ ܕܢܛܪܬܐ"، ܡܛܠ ܕܐܝܢܐ ܕܦܪܣܡܠܗ ܠܐ ܒܥܐ ܗܘܐ ܡܢ ܟܠ ܐܡܢ ܦܘܫܩܐ ܝܕܥܢܝܐ؛ ܠܐ ܝܕܝܥܘܬܐ ܫܪܝܪܬܐ "ܥܣܩܐ ܝܠܗ̇ ܠܡܛܝܐ"، ܡܛܠ ܕܐܢܫ̈ܐ ܟܡܫܬܘܕܥܝ ܡܢ ܪܝܫ ܡܢ ܕܝܠܝ̈ܬܐ ܐܚܪ̈ܢܝܬܐ ܝܢ ܡܢ ܨܠܝܒܘܬܐ ܕܓܙ̈ܐ؛ ܘܡܛܠ ܗܕܐ ܙܘܥܪܐ ܕܝܗܝ̈ܒܬܐ – ܟܢܫܐ ܒܣ ܕܡܐ ܕܦܘܫܩܐ ܟܒܥܐ: ܩܐ ܪܓܫܐ ܟܠܢܝܐ ܠܐ ܣܢܝܩ ܝܠܗ ܠܕܘܟܬܐ ܚܬܝܬܬܐ ܘܠ-profile ܓܡܝܪܐ. ܘ-Salganik (2018) ܥܠ ܡܐ ܕܫܚܠܦܠܗ: ܚܝܠܐ ܕܒܨܘ̈ܝܐ – "ܡܨܝܐܘܬܐ ܕܥܒܕܬܐ ܕܡܕܡ̈ܐ ܠܐܢܫ̈ܐ ܕܠܐ ܫܠܡܘܬܐ ܕܝܠܗܘܢ ܘܐܦ ܕܠܐ ܝܕܥܬܐ ܕܝܠܗܘܢ" – ܪܒܠܗ، ܘܢܡܘ̈ܣܐ ܠܐ ܓܠܝܠܗܘܢ ܒܗܝ̇ ܡܫܘܚܬܐ (ܦܐܬܐ 288)؛ ܐܪܒܥܐ ܫܪ̈ܫܐ ܕܡܘܕܥܢ̈ܘܝܬܐ ܕ-Belmont ܘ-Menlo – ܐܝܩܪܐ ܠܐܢܫܐ، ܝܘܬܪܢܐ (ܠܐ ܥܒܕܬܐ ܕܚܒܠܐ، ܡܪܒܝܬܐ ܕܝܘܬܪܢܐ ܘܡܙܥܪܬܐ ܕܚܒܠܐ)، ܟܐܢܘܬܐ ܓܘ ܦܘܠܓܐ ܕܛܥܢܐ ܘܕܝܘܬܪܢܐ، ܘܐܝܩܪܐ ܠܢܡܘܣܐ ܘܠܛܒܬܐ ܕܥܡܐ (ܦܐ̈ܬܐ 294-299)؛ ܢܡܘܣܐ ܥܒܕܢܝܐ "ܚܕ ܐܣܟܝܡܐ ܕܫܠܡܘܬܐ ܩܐ ܪܘܒܐ ܕܒܘܨ̈ܝܐ" (ܦܐܬܐ 303)؛ ܣܘܟܢܐ ܕܝܕܥܬܐ – ܚܒܠܐ ܡܢ ܓܠܝܘܬܐ ܕܝܕܥܬܐ – ܝܠܗ "ܣܘܟܢܐ ܕܡܬܚܙܐ ܝܬܝܪ ܡܢ ܟܠ ܓܘ ܒܘܨܝܐ ܟܢܫܝܐ، ܪܒܠܗ ܒܣܓܝ، ܘܥܣܩܐ ܝܠܗ ܝܬܝܪ ܡܢ ܟܠ ܠܣܘܟܠܐ" (ܦܐܬܐ 307)؛ ܘܬܠܬܐ ܡܠܟ̈ܐ: ܓܘܕܐ ܕܐܝܬܝܩܐ ܝܠܗ̇ "ܐܪܥܐ، ܠܐ ܬܛܠܝܠܐ"؛ ܣܝܡܘܢ ܓܢܒܘܟܘܢ ܓܘ ܣܐܢ̈ܐ ܕܟܠ ܐܚܪ̈ܢܐ؛ ܘܚܫܘܒܘܢ ܥܠ ܐܝܬܝܩܐ ܐܝܟ ܣܪܛܐ ܘܠܐ ܐܝܟ ܬܪܝܢ ܦܠ̈ܓܐ (ܦܐ̈ܬܐ 321-324).
ܠܘܚܐ 7. ܟܢܫܐ ܕܝܗܝ̈ܒܬܐ ܕܝܓܝܛܠܝ̈ܬܐ
| ܡܐܢܐ | ܡܘܕܝ ܟܥܒܕ | ܐܦܣܢܘܬܐ ܘܛܝܡܐ | ܡܨܥܬܐ | ܡܥܝܪ̈ܢܘܬܐ (notes) |
|---|---|---|---|---|
| Qualtrics | ܐܬܪܐ (platform) ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ ܩܐ ܬܘܩ̈ܢܐ: ܗܘܢܐ ܕܫܘܪ̈ܬܐ (skip logic)، randomization، panels، ܡܦܩܬܐ (export) ܠ-SPSS. | ܒܦܪܥܢܐ | ܒܪܐܘܙܪ | ܠܝܬ ܪܫܝܡܬܐ ܕܛܝ̈ܡܐ ܕܥܡܐ؛ ܐܦܣܢܘ̈ܝܬܐ ܕܩܡܦܘܣ ܡܬܚܙܝ̈ܢܐ ܝܢܐ ܣܓܝ ܓܘ ܐܝܣܪܐܝܠ. ܥܘܕܪܢܐ ܩܐ ܥܒܪܝܐ ܘ-RTL ܐܝܬ ܒܫܪܪܐ (ܠܐ ܐܡܝܪܐ ܓܘ ܦܐܬܐ ܩܕܡܝܬܐ). |
| LimeSurvey | ܡܐܢܐ ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ ܒܪܡܙܐ ܦܬܝܚܐ: ܬܘܩܢܐ ܕܝܠܘܟܘܢ ܝܢ ܥܢܢܐ (cloud) ܒܦܪܥܢܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ | GPL. ܡܦܩܬܐ (export) ܬܪܝܨܬܐ ܠ-SPSS (.sav + ܣܝܢܬܐܟܣ). ܥܪܒܝܐ ܐܝܬܠܗ̇ ܥܘܕܪܢܐ – ܐܝܬ RTL؛ ܥܒܪܝܐ ܠܐ ܪܫܝܡܬܐ ܝܠܗ̇ ܓܘ ܦܐܬܐ ܩܕܡܝܬܐ. |
| Google Forms | ܒܢܝܢܐ ܕܛܘ̈ܦܣܐ ܘܒܘܨ̈ܝܐ ܕܫܘܐ̈ܠܐ ܡܓܢ ܥܡ ܡܦܩܬܐ (export) ܠ-Sheets. | ܡܓܢ (ܩܦܝܠܐ) | ܒܪܐܘܙܪ | ܡܘܢܥܐ ܥܬܝܩܐ google.com/forms ܟܡܫܕܪ ܠܐܟܐ. ܩܐ ܒܘܨܝܐ ܦܫܝܛܐ؛ ܠܝܬ ܗܘܢܐ (logic) ܡܩܕܡܐ ܝܢ ܫܘܠܛܢܐ ܥܠ ܕܘܡܝܐ (sample). |
| SurveyMonkey | ܐܬܪܐ (platform) ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ ܕܡܬܚܙܐ ܣܓܝ ܥܡ ܛܘ̈ܦܣܐ (templates) ܘܕܝܠܝ̈ܬܐ ܕ-AI. | ܡܓܢ + ܒܦܪܥܢܐ | ܒܪܐܘܙܪ | ܥܒܪܝܐ ܠܐ ܝܠܗ̇ ܒܝܢܝ 15 ܠܫܢ̈ܐ ܕܡܨܥܬܐ (interface). ܬܘܩܢܐ ܡܓܢ ܟܪܝܐ ܝܠܗ ܒܫܘܐ̈ܠܐ ܘܒܦܘܢ̈ܝܐ. |
| Prolific | panel ܕܡܫܬܘܬܦ̈ܢܐ ܓܘ ܫܒܝܟܬܐ ܩܐ ܒܘܨܝܐ ܡܕܪܫܝܐ، ܥܡ ܡܨܠܠܢܘܬܐ (filter) ܕܥܡܐ (demographic) ܘܦܘܪܥܢܐ ܟܐܢܐ. | ܒܦܪܥܢܐ | ܒܪܐܘܙܪ | ܦܘܪܥܢܐ ܩܐ ܡܫܬܘܬܦܢܐ + ܐܓܪܐ ܕܬܫܡܫܬܐ. ܕܘܡܝܢ ܚܕܬܐ prolific.com. panel ܒܝܢ-ܐܘܡܬܢܝܐ – ܠܐ ܐܝܣܪܐܝܠܝܐ. |
| Beautiful Soup | ܟܬܒܘܬܐ ܕܪܡܙܐ (library) ܕ-Python ܩܐ ܦܘܪܩܐ ܕ-HTML ܘܡܦܩܬܐ ܕܝܗܝ̈ܒܬܐ ܡܢ ܦܐ̈ܬܐ ܕܐܢܛܪܢܝܬ. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܢܘܣܚܐ 4.14 (2025). ܕܪܓܐ ܩܕܡܝܐ ܓܘ scraping؛ ܩܐ ܟܡܝ̈ܘܬܐ ܪ̈ܒܬܐ – Scrapy. |
| Scrapy | ܛܘܦܣܐ ܕ-Python ܠܐ ܡܬܢܝܐ ܒܙܒܢܐ (asynchronous) ܩܐ crawling ܘ-scraping ܒܡܫܘܚܬܐ ܪܒܬܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܢܘܣܚܐ 2.17 (2026). ܟܡܝܩܪ robots.txt ܐܝܟ ܓܘܒܝܐ ܡܩܕܡܐ (default) – ܫܒܘܩܘܢ ܗܕܟܐ. |
| Playwright | ܥܒܕܐ ܒܚܘܕܝܗ ܕܒܪܐܘܙܪ (automation) (Chromium, Firefox, WebKit) – ܩܐ ܣܐܝ̈ܛܐ ܕܒܢܝ̈ܐ ܝܢܐ ܒ-JavaScript. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܕ-Microsoft. ܡܐܢܐ ܟܠܢܝܐ ܕܒܘܚܪ̈ܢܐ (testing)، ܡܘܬܪܢܐ ܩܐ scraping ܕܣܐܝ̈ܛܐ ܕܡܬܬܙܝܥܝ (dynamic)؛ Python ܘ-JavaScript. |
| 4CAT + Zeeschuimer | ܐܚܕܐ ܘܦܘܫܩܐ ܕܡ̈ܠܐ ܡܢ ܡܨܝ̈ܕܬܐ ܟܢܫ̈ܝܬܐ ܕܠܐ ܟܬܝܒܬܐ ܕܪܡܙܐ: Zeeschuimer (ܬܘܣܦܬܐ ܕ-Firefox) ܟܐܚܕ ܓܘ ܙܒܢܐ ܕܓܘܠܫܐ، 4CAT ܟܦܫܩ. | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ | ܡܕܪܫܬܐ ܥܠܝܬܐ ܕ-Amsterdam (DMI). ܟܒܥܐ ܢܘܣܚܐ ܡܕܪܫܝܐ ܝܢ ܬܘܩܢܐ ܕ-Docker. TikTok، Instagram، Threads، X، Telegram، Bluesky. |
| YouTube Data Tools | ܡܦܩܬܐ ܕܝܗܝ̈ܒܬܐ ܕܩܢ̈ܐ (channels)، ܒܝܕ̈ܝܘ ܘܡܥܝܪ̈ܢܘܬܐ ܡܢ YouTube ܒܝܕ API ܪܫܡܝܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ | Bernhard Rieder (DMI). ܡܢܬܐ ܡܢ modules ܟܠܝܠܗܘܢ ܒܬܪ ܫܘܢ̈ܝܐ ܕ-API (2023). ܡܝܬܝܘܢ Rieder (2015). |
ܡܥܝܪܢܘܬܐ. ܡܐܢ̈ܐ ܕ-scraping (Beautiful Soup, Scrapy, Playwright) ܡܐܢ̈ܐ ܕܬܘܟܢܝܬܐ ܟܠܢ̈ܝܐ ܝܢܐ؛ ܢܡܘܣܝܘܬܐ ܘܐܝܬܝܩܐ ܕܡܦܠܚܢܘܬܐ ܕܝܠܗܘܢ ܦܣܝܩ̈ܐ ܝܢܐ ܠܦܘܬ ܣܐܝܛ ܕܡܬܬܫܩܠ ܘܢܝܫܐ ܕܒܘܨܝܐ، ܠܐ ܠܦܘܬ ܡܐܢܐ.
8. ܣܛܐܛܝܣܛܝܩܐ ܘܝܘܠܦܢܐ ܕܡܟܝܢܐ
ܓܢܣܐ ܕܐܗܐ ܣܐܝܛ ܒܢܦܫܗ ܦܐܝܐ ܝܠܗ ܠܗ̇، ܘܡܛܠ ܗܕܐ ܡܥܝܪܢܘܬܐ ܚܫܝܚܬܐ: ܩܐ ܟܠ ܒܘܚܪ̈ܢܐ ܕܐܝܬ ܠܗܘܢ ܠܐܟܐ ܡܚܫܒܢܐ (calculator) – ܦܐܬܐ ܕܡܚܫܒܢܐ ܝܠܗ̇ ܡܐܢܐ، ܓܘ ܒܪܐܘܙܪ ܘܕܠܐ ܕܝܗܝ̈ܒܬܐ ܫܒܩܝ ܚܘܫܒܢܐ (ܚܙܝܡܘܢ ܐܣܘܪ̈ܐ ܓܘ ܫܘܠܡܐ). ܐܗܐ ܠܘܚܐ (table) ܩܐ ܡܐ ܕܠܥܠ ܡܢܗ ܝܠܗ: ܡܘܕܝ̈ܠܐ ܕܣܓܝ ܕܪ̈ܓܐ (multilevel)، ܝܘܠܦܢܐ ܕܡܟܝܢܐ (machine learning)، SEM ܓܡܝܪܐ، ܘܩܐ ܐܝܢܐ ܕܒܥܐ ܬܘܟܢܝܬܐ ܓܡܝܪܬܐ. ܦܘܪܫܢܐ ܪܫܝܐ ܝܠܗ ܒܝܢܝ ܣܛܐܛܝܣܛܝܩܐ (ܦܘܫܩܐ: ܐܝܢܐ ܡܫܬܚܠܦܢܐ ܟܥܒܕ ܡܥܒܕܢܘܬܐ ܘܟܡܐ) ܘܝܘܠܦܢܐ ܕܡܟܝܢܐ (ܡܢܒܝܢܘܬܐ (prediction): ܡܘܕܝ ܒܕ ܗܘܝܐ ܠܚܙܝܬܐ (observation) ܚܕܬܐ) – ܬܪܝܢ ܢܝܫ̈ܐ ܦܪ̈ܝܫܐ ܕܟܒܥܝ ܫܘܪܪܐ ܦܪܝܫܐ، ܐܦ ܐܝܡܢ ܕܡܘܕܝܠ ܫܘܝܐ ܝܠܗ. ܐܗܐ ܦܘܪܫܢܐ، ܨܢܘܪܐ (pipeline) ܡܢ ܪܝܫܐ ܠܪܝܫܐ، ܡܘܕܝ̈ܠܐ – ܡܢ ܐܝܠܢܐ ܕܦܣ̈ܩܬܐ (decision tree) ܗܠ ܡܨܝܕܬܐ ܕܢܝܘܪܘܢ̈ܐ (neural network) – ܘܡܐܢ̈ܐ ܕܝܠܗܘܢ، ܓܘ ܦܐܬܐ ܝܘܠܦܢܐ ܕܡܟܝܢܐ ܩܐ ܒܨܘܝܐ ܟܢܫܝܐ؛ ܡܚܘ̈ܝܢܐ، ܫܘܪܪܐ ܡܚܠܦܢܐ (cross-validation)، ܕܠܝܦܘܬܐ ܕܝܗܝ̈ܒܬܐ (data leakage) ܘܝܗܝ̈ܒܬܐ ܕܠܐ ܝܢܐ ܠܐ ܬܠܝ̈ܬܐ – ܓܘ ܡܚܘ̈ܝܢܐ ܕܥܒܕܐ ܘܫܘܪܪܐ؛ ܦܘܫܩܐ ܕܥܠ̈ܠܬܐ، ܕܡܢܘ̈ܬܐ ܘܕܥܢܩܘ̈ܕܐ – ܝܘܠܦܢܐ ܕܠܐ ܡܫܬܚܠܦܢܐ ܬܠܝܐ – ܓܘ ܝܘܠܦܢܐ ܕܠܐ ܡܕܒܪܢܐ؛ ܠܘܚܐ 8 ܕܠܐܟܐ ܟܦܝܫ ܠܘܚܐ ܕܬܘܟ̈ܢܝܬܐ ܣܛܐܛܝܣܛܝܩ̈ܝܬܐ.
ܙܘܓܐ JASP / jamovi ܫܘܝܐ ܝܠܗ ܠܚܘܪܐ ܦܪܝܫܐ: ܬܪܘܝܗܝ ܚܠ̈ܦܐ ܡܓܢ̈ܝܐ ܕ-SPSS ܝܢܐ ܥܡ ܡܨܥܬܐ ܓܪܦܝܬܐ، ܣܡܝܟ̈ܐ ܥܠ R، ܘܟܚܫܒܝ ܐܦ ܒܐܘܪܚܐ ܕ-Bayes. PSPP ܝܠܗ ܬܘܟܢܝܬܐ ܕܦܘܚܡܐ (reference) ܕܒܗ̇ ܡܫܪܪ̈ܐ ܝܢܐ ܡܢܘ̈ܬܐ ܡܢ ܐܗܐ ܣܐܝܛ – ܡܓܢ، ܘܟܡܪܗܛ ܣܝܢܬܐܟܣ ܕ-SPSS.
ܫܪܫܐ ܩܕܡ ܡܐܢܐ. Dawson (2020، ܦܐ̈ܬܐ 194-199) ܟܡܚܕܕܐ ܝܘܠܦܢܐ ܕܡܟܝܢܐ ܐܝܟ ܐܠܓܘܪܝܬܡ̈ܐ ܕ"ܝܠܦܝ ܡܢ ܚܘܫ̈ܒܢܐ ܕܩܕܡ ܩܐ ܫܩܠܬܐ ܕܦܣ̈ܩܬܐ ܘܡܢܒܝܢ̈ܘܝܬܐ ܡܬܢ̈ܝܬܐ ܕܠܐ ܟܬܝܒܬܐ ܕܪܡܙܐ ܓܠܝܬܐ ܣܡܝܟܬܐ ܥܠ ܢܡܘ̈ܣܐ"، ܡܕܒܪܐ (supervised؛ ܡܥܠܬܐ ܘܡܦܩܬܐ ܪܫܝܡ̈ܐ) ܝܢ ܠܐ ܡܕܒܪܐ – ܘܐܗܐ ܚܬܝܬܐܝܬ ܦܘܪܫܢܐ ܝܠܗ ܡܢ ܡܚܫܒ̈ܢܐ ܕܣܐܝܛ، ܕܓܘܝܗܝ ܢܡܘܣܐ ܓܠܝܐ ܝܠܗ. Drucker ܘ-Albrezzi (2026، ܦܐܬܐ 1) ܟܩܪܝ ܠܦܘܠܚܢܐ "ܩܘܦܬܐ ܐܘܟܡܬܐ ܕܥܒܕܐ ܕܝܓܝܛܠܝܐ"، ܡܛܠ ܕܪܘܒܐ ܕܝܠܗ ܟܡܬܥܒܕ ܒܡܐܢ̈ܐ ܡܛܝܒ̈ܐ ܕܥܒܕܐ ܕܝܠܗܘܢ ܟܣܝܐ ܝܠܗ، ܘܟܡܙܗܪܝ ܕܟܡܐ ܕܦܘܠܚ̈ܢܐ ܚܪ̈ܝܦܐ ܝܢܐ ܝܬܝܪ ܘܥܠܝܠ̈ܐ ܝܢܐ ܓܘܝܗܝ ܝܘܠܦܢܐ ܕܡܟܝܢܐ ܘ-AI "ܪܘܒܐ ܕܙܒ̈ܢܐ ܟܡܚܝܠܝ ܡܣܒ ܒܐܦ̈ܐ (bias) ܕܒܢܝܐ ܝܠܗ ܓܘ ܡܘܕܝܠ ܕܝܠܗܘܢ" (ܦܐܬܐ 2). ܐܦ ܥܠ ܦܘܫܩܐ ܕܥܢܩܘ̈ܕܐ (cluster analysis) Dawson ܟܫܐܠܐ (ܦܐ̈ܬܐ 31-37): "ܡܨܝܚ ܕܬܟܠܚ ܥܠ ܬܘܟܢܝܬܐ، ܥܠ ܡܐܢ̈ܐ ܘܥܠ ܐܠܓܘܪܝܬܡ̈ܐ؟" – ܘܟܡܩܪܒܐ ܕܒܚܪܚ ܒܥܘܕܪܢܐ ܕܬܘܟܢܝܬܐ ܐܚܪܬܐ، ܕܐܗܐ ܚܬܝܬܐܝܬ ܝܠܗ ܫܪܫܐ ܕܨܠܝܒܘܬܐ ܕܐܗܐ ܣܐܝܛ (PSPP، R، Python ܥܠ ܗܢܝ ܝܗܝ̈ܒܬܐ). ܘܡܘܕܝ ܝܗܝ̈ܒܬܐ ܪ̈ܒܬܐ ܠܐ ܟܝܗܒܝ ܡܢ ܢܦܫܝܗܝ – ܥܠܬܢܘܬܐ (causality): Salganik (2018، ܦܐ̈ܬܐ 50-61) ܟܡܚܘܐ ܕܟܝ "ܟܩܪܒܚ ܠܢܣܝ̈ܘܢܐ ܕܠܐ ܡܨܝܚ ܕܥܒܕܚ" ܒܬܪܬܝܢ ܐܘܪ̈ܚܬܐ ܕܙܒܢܐ ܕܝܓܝܛܠܝܐ ܦܬܝܠܗܝ̇، ܢܣܝ̈ܘܢܐ ܛܒܝܥ̈ܝܐ ܘܦܐܝܘܬܐ (matching) – ܘܬܪܘܝܗܝ ܟܫܪܝ ܒܣܒܪ̈ܐ ܕܣܢܝܩ ܝܠܗ ܕܡܬܟܬܒܝ، ܠܐ ܒܡܐܢܐ. ܘܩܐ ܡܘܕܝ̈ܠܐ ܪ̈ܒܐ ܕܠܫܢܐ (LLMs)، ܕܡܦܩܬܐ ܬܪܝܢܝܬܐ ܕ-Drucker ܘ-Albrezzi ܟܝܗܒܐ ܠܗܘܢ ܨܚܚܐ (12a)، ܬܪܝܢ ܣܪ̈ܛܐ ܩܐ ܓܘܒܝܐ ܕܡܘܕܝܠ: ܦܬܝܚܐ ܝܢ ܩܦܝܠܐ، ܘܐܬܪܢܝܐ ܝܢ ܪܚܝܩܐ. ܡܘܕܝܠ ܩܦܝܠܐ ܕܟܦܠܚ ܥܠ ܣܝܪܒܪ ܕܫܪܟܘܬܐ ܟܐܡܪ ܕ"ܝܗܝ̈ܒܬܐ ܕܝܘܟܘܢ ܐܚܝ̈ܕܬܐ ܘܡܦܘܠܚ̈ܬܐ ܝܢܐ ܓܘ ܣܝܪ̈ܒܪܐ ܕܩܢܝܢܐ"، ܘܚܠܦܐ – ܡܘܕܝܠ ܦܬܝܚܐ ܕܟܡܚܬܬܚ ܘܟܡܪܗܛܚ ܐܬܪܢܐܝܬ (ܡܬܠܐ ܓܘ Ollama) – ܩܐ ܐܝܢܐ ܕܠܐ ܒܥܐ ܕܡܫܘܬܦ ܚܘܡܪܐ؛ ܘܛܟܣܐ ܕܡܕܥܪܢܘܬܐ (retrieval) ܕܙܢܐ ܕ-RAG، ܕܟܦܢܐ ܒܣ ܡܢ ܓܙܐ ܕܒܨܘܝܐ ܚܕܕܠܗ، ܚܬܝܬܐ ܝܠܗ ܝܬܝܪ ܘܦܐܝܐ ܝܠܗ ܩܐ ܝܗܝ̈ܒܬܐ ܪܓܝܫ̈ܬܐ ܝܢ ܢܛܝܪ̈ܬܐ (ܦܐ̈ܬܐ 118-119). ܘ-hallucinations ܬܘܒ ܟܗܘܝܐ: ܟܠ ܡܦܩܢܐ (output)، ܐܦ ܐܝܡܢ ܕܟܡܬܚܙܐ ܚܬܝܬܐ، "ܣܢܝܩ ܝܠܗ ܕܡܒܘܨܝܐ، ܕܡܒܘܚܪܐ ܘܕܡܦܘܚܡܐ ܗܘܐ ܥܡ ܡܒܘ̈ܥܐ ܡܗܝܡܢ̈ܐ ܕܝܕܝܥ̈ܐ ܝܢܐ" (ܦܐܬܐ 119). ܐܝܬܝܩܐ ܘܢܡܘܣܐ (Dawson, 2020, pp. 194-199): "ܝܘܠܦܢܐ ܕܡܟܝܢܐ ܠܐ ܦܢܝܐ ܝܠܗ ܐܝܬܝܩܐܝܬ؟" – ܐܝܡܢ ܕܡܘܕܝܠ ܕܡܢܒܝܢܘܬܐ ܟܝܠܕ ܦܣ̈ܩܬܐ ܟܢܫ̈ܝܬܐ، ܣܢܝܩ ܝܠܗ ܠܟܐܢܘܬܐ (fairness)، ܡܫܐܠܢܘܬܐ (accountability) ܘܓܠܝܘܬܐ (transparency) (Veale & Binns, 2017, as cited in Dawson). Drucker ܘ-Albrezzi (2026، ܦܐ̈ܬܐ 120-121) ܟܡܘܣܦܝ: "ܟܠ ܦܘܠܚܢܐ ܕܓܘܗ ܒܢܝ̈ܢܫܐ ܟܡܬܡܢܝ، ܟܡܬܛܟܣܝ ܝܢ ܟܡܬܚܫܒܝ ܐܝܟ ܝܗܝ̈ܒܬܐ ܟܡܣܟܢ ܒܐܒܕܢܐ ܕܐܢܫܘܬܐ ܕܝܠܗܘܢ ܕܢܦܫܐ"؛ ܡܒܘܥܐ ܕܝܗܝ̈ܒܬܐ (provenance) ܕܡܘܕܝ̈ܠܐ "ܐܘܟܡܐ ܝܠܗ ܒܣܓܝ" – ܛܘ̈ܦܣܐ ܕܝܘܠܦܢܐ (training sets) ܕܩܢܝܢܐ ܝܢܐ، ܘܐܢ ܠܐ ܝܠܗ ܛܟܣܐ ܕ-RAG ܠܐ ܝܕܥܚ ܥܠ ܐܝܢܝ ܡܒܘ̈ܥܐ ܣܡܝܟܐ ܝܠܗ ܡܦܩܢܐ ܘܕܟܝ ܡܬܩܠ̈ܐ ܗܘܘ؛ ܘܓܘ ܫܪ̈ܛܐ ܕܡܦܠܚܢܘܬܐ (Terms of use) ܕܡܐܢ̈ܐ ܣܓܝ̈ܐܐ ܡܦܠܚܢܐ ܟܡܣܟܡ ܕ-prompts ܘܡܦܩ̈ܢܐ ܕܝܠܗ ܒܕ ܡܦܠܚܝ ܩܐ ܝܘܠܦܢܐ ܕܒܬܪ ܗܕܐ ܘܐܦ ܒܕ ܡܫܬܕܪܝ ܠܫܘܬܦ̈ܐ – ܡܐ ܕܠܐ ܫܠܝܛܐ ܝܠܗ ܠܥܒܕܬܐ ܒܝܗܝ̈ܒܬܐ ܕܡܫܬܘܬܦ̈ܢܐ.
ܠܘܚܐ 8. ܣܛܐܛܝܣܛܝܩܐ ܘܝܘܠܦܢܐ ܕܡܟܝܢܐ
| ܡܐܢܐ | ܡܘܕܝ ܟܥܒܕ | ܐܦܣܢܘܬܐ ܘܛܝܡܐ | ܡܨܥܬܐ | ܡܥܝܪ̈ܢܘܬܐ (notes) |
|---|---|---|---|---|
| R + RStudio | ܠܫܢܐ ܕܣܛܐܛܝܣܛܝܩܐ ܕܡܕܪ̈ܫܝܬܐ، ܥܡ 20,000+ ܨܪ̈ܪܐ (packages)؛ RStudio (Posit) – ܕܘܟܬܐ ܕܥܒܕܐ ܡܩܒܠܬܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܪܡܙܐ | R 4.6 (2026). RStudio: posit.co/products/open-source/rstudio. ܦܣ̈ܩܐ ܕ"ܘܕܟܝ ܟܥܒܕܚ ܐܗܐ ܒ-R" ܓܘ ܣܐܝܛ ܟܣܒܪܝ ܠܗ̇. |
| Python: Anaconda + Jupyter | ܦܘܠܓܐ (distribution) ܕ-Python ܩܐ ܝܕܥܬܐ ܕܝܗܝ̈ܒܬܐ (Anaconda) ܘܟܬ̈ܒܐ interactive (Jupyter) ܕܟܡܚܠܛܝ ܪܡܙܐ، ܡܦܩܢܐ (output) ܘܡ̈ܠܐ. | ܡܓܢ + ܒܦܪܥܢܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܪܡܙܐ | Jupyter – ܪܡܙܐ ܦܬܝܚܐ. Anaconda ܡܓܢ ܩܐ ܝܚܝ̈ܕܝܐ ܘܩܐ ܬܘܩ̈ܢܐ ܙܥܘܪ̈ܐ؛ ܬܘܩ̈ܢܐ ܪ̈ܒܐ – ܐܦܣܢܘܬܐ. ܚܠܦܐ ܩܠܝܠܐ: Miniforge. |
| JASP | ܬܘܟܢܝܬܐ ܣܛܐܛܝܣܛܝܩܝܬܐ ܡܓܢ ܕܕܡܝܐ ܠ-SPSS، ܥܡ ܦܘܫ̈ܩܐ ܩܠܐܣܝܩ̈ܝܐ ܘܕ-Bayes ܚܕ ܓܢܒ ܚܕ. | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ | ܢܘܣܚܐ 0.98 (2026)، ܡܕܪܫܬܐ ܥܠܝܬܐ ܕ-Amsterdam. ܡܦܩܢܐ (output) ܓܘ ܐܣܟܝܡܐ APA ܒܢܝܐ ܓܘܗ. |
| jamovi | ܓܠܝܘܢܐ (sheet) ܣܛܐܛܝܣܛܝܩܝܐ ܡܓܢ ܣܡܝܟܐ ܥܠ R، ܥܠ ܚܘܫܒܢܐ ܝܢ ܓܘ ܒܪܐܘܙܪ (jamovi Cloud). | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܒܪܐܘܙܪ | ܢܘܣܚܐ 2.7. ܟܡܚܘܐ ܪܡܙܐ ܕ-R ܕܒܣܬܪ ܟܠ ܦܘܫܩܐ – ܓܫܪܐ ܛܒܐ ܩܐ ܝܘܠܦܢܐ ܕ-R. |
| PSPP | ܚܠܦܐ ܡܓܢ ܕ-SPSS ܡܢ ܦܪܘܝܩܬ GNU: ܡܨܥܬܐ ܓܪܦܝܬܐ ܘܣܝܢܬܐܟܣ ܕܦܐܐ ܠ-SPSS. | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܪܡܙܐ | ܢܘܣܚܐ 2.1 (2026). ܟܡܪܗܛ ܦܐܝ̈ܠܐ .sps ܕܣܐܝܛ ܟܡܦܩ (ܕܠܐ GGRAPH ܘ-ALTER TYPE). ܡܐܢܐ ܕܨܠܝܒܘܬܐ (cross-check) ܕܣܐܝܛ. |
| IBM SPSS Statistics | ܨܪܪܐ ܣܛܐܛܝܣܛܝܩܝܐ ܬܓܪܝܐ ܕܡܬܚܙܐ ܝܬܝܪ ܓܘ ܝܕ̈ܥܬܐ ܕܟܢܫܐ؛ ܬܘܟܢܝܬܐ ܕܦܘܚܡܐ (reference) ܕܐܗܐ ܣܐܝܛ. | ܒܦܪܥܢܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܪܡܙܐ | ܡܢܘܝ (subscription) ܡܢ 99 ܕܘܠܪ̈ܐ ܒܝܪܚܐ؛ ܐܦܣܢܘ̈ܝܬܐ ܕܩܡܦܘܣ ܘܕܬܠܡܝ̈ܕܐ (GradPack). ܢܘܣܚܐ 31-32. |
| Stata | ܨܪܪܐ ܣܛܐܛܝܣܛܝܩܝܐ ܬܓܪܝܐ ܡܚܠܛܐ، ܚܝܠܢܐ ܝܬܝܪ ܓܘ panel ܘܓܘ ܝܕܥܬܐ ܕܡܕܒܪܢܘܬܐ ܕܒܝܬܐ (economics). | ܒܦܪܥܢܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܪܡܙܐ | Stata 19. ܐܦܣܢܘ̈ܝܬܐ ܕܬܠܡܝ̈ܕܐ ܘܕܩܡܦܘܣ (GradPlan). |
| scikit-learn | ܟܬܒܘܬܐ ܕܪܡܙܐ ܕܝܘܠܦܢܐ ܕܡܟܝܢܐ ܕ-Python: ܦܘܪܫܐ ܠܓܢ̈ܣܐ (classification)، ܪܝܓܪܫܢ (regression)، ܥܢܩܘ̈ܕܐ (clusters)، ܓܘܒܝܐ ܕܡܘܕܝܠ. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܢܘܣܚܐ 1.9. API ܫܘܝܐ ܕܟܠ ܟܬܒ̈ܘܝܬܐ ܐܚܪ̈ܢܝܬܐ ܟܡܕܡܝ ܠܗ. |
| statsmodels | ܡܘܕܝ̈ܠܐ ܣܛܐܛܝܣܛܝܩ̈ܝܐ ܓܘ Python ܒܟܬܝܒܬܐ ܕܡܥܠܝ̈ܬܐ ܐܝܟ R، ܥܡ ܡܦܩܢܐ (output) ܓܡܝܪܐ ܕܒܘܚܪ̈ܢܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܢܘܣܚܐ 0.15 (2026). ܡܐܢܐ ܕܨܠܝܒܘܬܐ (cross-check) ܕܣܐܝܛ ܩܐ ܪܝܓܪܫܢ ܣܪܛܢܝܐ ܘܠܘܓܝܣܛܝܩܝܐ. |
| lavaan | ܨܪܪܐ ܕ-R ܩܐ ܡܘܕܝ̈ܠܐ ܕܫܘܝ̈ܘܬܐ ܒܢܝܢܝ̈ܬܐ (structural equations): CFA، ܦܘܫܩܐ ܕܫܒ̈ܝܠܐ (path analysis)، SEM ܓܡܝܪܐ، ܡܘܕܝ̈ܠܐ ܕܪܒܝܬܐ (growth models). | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܢܘܣܚܐ 0.7 (2026)، Yves Rosseel، Ghent. ܡܫܩܠܢܐ ܕܦܘܚܡܐ (reference) ܕܡܘܕܘܠ ܕ-SEM ܓܘ ܣܐܝܛ. ܡܝܬܝܘܢ Rosseel (2012). |
| Orange | ܝܘܠܦܢܐ ܕܡܟܝܢܐ ܘ-visualization ܒܟܬܝܒܬܐ ܕܪܡܙܐ ܚܙܝܬܐ – ܐܣܘܪܐ ܕܩܘ̈ܦܣܐ، ܕܠܐ ܪܡܙܐ؛ ܬܘܣܦܬܐ ܩܐ ܚܦܪܬܐ ܕܡ̈ܠܐ (text mining). | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ | ܢܘܣܚܐ 3.40، Ljubljana. ܐܘܪܚܐ ܛܒܬܐ ܡܢ ܟܠ ܕܡܠܦܚ ܝܘܠܦܢܐ ܕܡܟܝܢܐ ܕܠܐ ܟܬܝܒܬܐ ܕܚܕ ܣܕܪܐ. |
| KNIME | ܐܬܪܐ (platform) ܕܝܕܥܬܐ ܕܝܗܝ̈ܒܬܐ ܣܡܝܟܐ ܥܠ nodes؛ ܢܘܣܚܐ ܕܚܘܫܒܢܐ (desktop) ܡܓܢ، Hub ܕܫܘܬܦܘܬܐ ܒܦܪܥܢܐ. | ܡܓܢ + ܒܦܪܥܢܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ | KNIME Analytics Platform – GPL. ܩܐ ܨܢܘܪ̈ܐ (pipelines) ܐܪ̈ܝܟܐ ܕܦܘܠܚܢܐ ܕܟܕܥܪܝ. |
ܡܥܝܪܢܘܬܐ. R، Python ܘܪܘܒܐ ܕܟܬܒ̈ܘܝܬܐ ܕܪܡܙܐ – ܪܡܙܐ ܦܬܝܚܐ. SPSS ܘ-Stata – ܬܓܪ̈ܝܐ ܥܡ ܐܦܣܢܘ̈ܝܬܐ ܕܬܠܡܝ̈ܕܐ ܘܕܩܡܦܘܣ. ܡܐܢ̈ܐ ܕܨܠܝܒܘܬܐ (cross-check) ܕܣܐܝܛ: SPSS، PSPP، scipy/statsmodels (Python)، lavaan (R).
9. Visualization ܕܝܗܝ̈ܒܬܐ
ܬܠܬܐ ܕܪ̈ܓܐ: ܡܐܢ̈ܐ "ܕܠܐ ܪܡܙܐ" ܓܘ ܒܪܐܘܙܪ (Datawrapper، Flourish، RAWGraphs) ܩܐ ܨܘܪܬܐ ܡܣܪܗܒܬܐ ܘܡܝܩܪܬܐ ܩܐ ܡܦܪܣܡܢܘܬܐ؛ ܓܪܡܛܝܩܐ ܓܪܦܝܬܐ ܒܪܡܙܐ (ggplot2، Vega-Lite، Plotly) ܩܐ ܨܘܪܬܐ ܕܡܨܝܐ ܕܡܬܥܒܕܐ ܬܘܒ ܘܕܡܬܚܕܬܐ ܒܚܘܕܝܗ̇؛ ܘ-D3.js ܩܐ visualization ܡܦܐܝܬܐ ܕܠܝܬ ܠܗ̇ ܛܘܦܣܐ. ܩܐ ܟܬܝܒܬܐ ܕܦܘܫܩܐ-ܕܡܘܕܥܢܘܬܐ (analytical journalism) – Datawrapper ܝܠܗ ܡܐܢܐ ܕܒ̈ܬܐ ܕܚܒܪ̈ܐ، ܘܐܗܘ ܝܚܝܕܝܐ ܝܠܗ ܠܐܟܐ ܕܓܠܝܐܝܬ ܟܐܡܪ ܥܠ ܥܘܕܪܢܐ ܓܡܝܪܐ ܩܐ RTL ܘܩܐ ܥܒܪܝܐ.
ܩܐ ܨܘܪܬܐ ܡܕܪܫܝܬܐ ܠܦܘܬ APA (ܦܣ̈ܩܐ 7.22-7.28) – ܨܘܪ̈ܬܐ ܕܡܚܫܒ̈ܢܐ ܓܘ ܣܐܝܛ ܡܢ ܩܕܡ ܒܢܝ̈ܐ ܝܢܐ ܗܕܟܐ؛ ܩܐ R ܚܙܝܡܘܢ ܦܣܩܐ "ܘܕܟܝ ܟܥܒܕܚ ܐܗܐ ܒ-R" ܓܘ ܦܐܬܐ ܨܘܪܬܐ ܕܒܕܪܐ، ܥܡ ܦܘܫܪܐ ܩܐ ܢܘܩܙܬܐ ܕܥܒܪܝܐ (ܡܫܩܠܢܐ AGG).
ܫܪܫܐ ܩܕܡ ܡܐܢܐ. ܪܓܫܐ ܕܐܝܬ ܠܝܗܝ̈ܒܬܐ ܐܣܟܝܡܐ ܚܙܝܐ ܒܢܝܐ ܓܘܝܗܝ "ܚܙܘܐ ܕܓܠܐ ܝܠܗ" – ܟܠ ܣܕܪܐ ܡܨܝܚ ܕܡܚܘܚ ܠܗ ܒܥܣܪ̈ܐ ܕܛܘ̈ܦܣܐ، ܘܒܣ ܡܢܬܐ ܡܢܝܗܝ ܦܐܝ̈ܐ ܝܢܐ ܠܕܝܠܝ̈ܬܐ ܕܝܗܝ̈ܒܬܐ (Drucker & Albrezzi, 2026, p. 57)؛ "ܟܠ visualizations ܦܘܫ̈ܩܐ ܝܢܐ، ܠܐ ܚܘ̈ܝܐ ܕܥܒ̈ܕܐ" (ܦܐܬܐ 67). ܛܥܝ̈ܘܬܐ ܕܡܬܚܙܝܢ ܣܓܝ ܕܟܡܢܝܐ (ܦܐ̈ܬܐ 60-66): ܡܦܠܚܢܘܬܐ ܒܝܫܬܐ ܕܦܬܝܘܬܐ ܕܐܦܐ (area؛ ܐܝܡܢ ܕܛܝܡܐ ܟܥܦܦ ܘܐܦܐ ܪܒܐ ܐܪܒܥܐ ܐܥܦ̈ܐ – ܨܘܪܬܐ 7.5 ܕܝܠܗܘܢ)، ܡܬܡܫܚܢܘܬܐ ܕܠܐ ܟܝܢܐ (ܣܪܛܐ ܕܐܣܪ ܢܘܩ̈ܙܐ ܦܪ̈ܝܫܐ ܕܠܐ ܝܢܐ ܣܕܪܐ – ܨܘܪܬܐ 7.4a)، ܘܣܒܠܬܐ (scale) ܕܡܬܡܫܚܐ ܡܛܠ ܚܕ ܛܝܡܐ ܢܘܟܪܝܐ ܘܟܥܒܪܐ ܦܘܪ̈ܫܢܐ ܓܘ ܡܨܥܬܐ (ܨܘܪܬܐ 7.7). Dawson (2020، ܦܐ̈ܬܐ 86-92) ܟܡܘܣܦܐ ܡܣ̈ܒܝ ܒܐܦ̈ܐ (bias) ܕܠܐ ܝܢܐ ܓܪܦܝ̈ܐ: ܡܣܒ ܒܐܦ̈ܐ ܕܬܫܥܝܬܐ (ܓܘܒܝܐ ܕܬܫܥܝܬܐ ܕܟܡܬܚܘܝܐ)، visualization ܕܟܡܣܡܟܐ ܠ-ideology، ܘܠܫܢܐ ܕܟܦܠܛ ܐܢܫ̈ܐ. ܐܝܬܝܩܐ ܘܢܡܘܣܐ (ܬܡܢ): ܪܘܫܡܐ ܕܡܒܘ̈ܥܐ ܕܝܗܝ̈ܒܬܐ ܓܘ ܨܘܪܬܐ ܒܢܦܫܗ̇، ܘܓܠܝܘܬܐ (transparency) ܕܕܪ̈ܓܐ ܕܒܢܝܢܐ – "ܕܟܝ ܒܕ ܡܫܪܪܝܬܘܢ ܕ-visualization ܠܐ ܒܕ ܡܕܒܪܐ ܠܫܘ̈ܠܡܐ ܛܥ̈ܝܐ؟"
ܠܘܚܐ 9. Visualization ܕܝܗܝ̈ܒܬܐ
| ܡܐܢܐ | ܡܘܕܝ ܟܥܒܕ | ܐܦܣܢܘܬܐ ܘܛܝܡܐ | ܡܨܥܬܐ | ܡܥܝܪ̈ܢܘܬܐ (notes) |
|---|---|---|---|---|
| Datawrapper | ܨܘܪ̈ܬܐ، ܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ ܘܠܘ̈ܚܐ interactive ܘ-responsive ܕܠܐ ܪܡܙܐ؛ ܡܐܢܐ ܕܒ̈ܬܐ ܕܚܒܪ̈ܐ. | ܡܓܢ + ܒܦܪܥܢܐ | ܒܪܐܘܙܪ | ܡܓܢ ܥܡ ܪܘܫܡܐ (credit)؛ Pro 21 ܕܘܠܪ̈ܐ ܒܝܪܚܐ. ܥܘܕܪܢܐ ܐܡܝܪܐ ܩܐ RTL ܘܩܐ ܥܒܪܝܐ ܓܘ ܟܠ visualizations. |
| Flourish | ܛܘ̈ܦܣܐ (templates) ܩܐ ܨܘܪ̈ܬܐ، ܨܘܪ̈ܬܐ ܕܐܬܪ̈ܘܬܐ ܘܬܫܥ̈ܝܬܐ ܕܝܗܝ̈ܒܬܐ interactive. | ܡܓܢ + ܒܦܪܥܢܐ | ܒܪܐܘܙܪ | ܕܝܠܗ ܕ-Canva. ܦܪܘܝ̈ܩܬܐ ܕܥܡܐ ܕܠܐ ܬܚܘܡܐ ܡܓܢ، ܥܡ ܪܘܫܡܐ (credit). |
| RAWGraphs | ܡܢ ܓܠܝܘܢܐ (sheet) ܠ-30 ܙܢ̈ܐ ܕܨܘܪ̈ܬܐ ܓܘ ܒܪܐܘܙܪ – ܥܡ ܙܢ̈ܐ ܕܠܝܬ ܓܘ ܐܩܣܠ (alluvial, bump, streamgraph). | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ | ܢܘܣܚܐ 2.0 (2025). ܝܗܝ̈ܒܬܐ ܟܦܝܫܝ ܓܘ ܒܪܐܘܙܪ. ܡܦܩܬܐ (export) ܕ-SVG ܩܐ ܬܘܩܢܐ. |
| Tableau Public | ܢܘܣܚܐ ܡܓܢ ܕ-Tableau ܩܐ ܒܢܝܢܐ ܕ-dashboards interactive ܘܡܦܪܣܡܢܘܬܐ ܕܝܠܗܘܢ. | ܡܓܢ (ܩܦܝܠܐ) | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܒܪܐܘܙܪ | ܟܠ ܡܐ ܕܟܡܦܪܣܡܚ – ܕܥܡܐ ܝܠܗ. ܩܐ ܝܗܝ̈ܒܬܐ ܪܓܝܫ̈ܬܐ – ܠܐ. |
| D3.js | ܟܬܒܘܬܐ ܕܪܡܙܐ ܕ-JavaScript ܒܕܪܓܐ ܢܚܝܬܐ ܩܐ visualization ܡܦܐܝܬܐ، ܡܬܬܙܝܥܢܝܬܐ (dynamic) ܘܣܡܝܟܬܐ ܥܠ ܝܗܝ̈ܒܬܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܢܘܣܚܐ 7.9 (2024). ܣܪܛܐ ܕܝܘܠܦܢܐ ܚܪܝܦܐ؛ ܦܐܪܐ – ܟܠ ܡܐ ܕܡܨܝܚ ܕܚܫܒܚ. |
| Plotly | ܟܬܒ̈ܘܝܬܐ ܕܪܡܙܐ ܕܨܘܪ̈ܬܐ interactive ܩܐ Python، R ܘ-JavaScript. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | MIT. ܟܬܒ̈ܘܝܬܐ ܡܓܢ̈ܝܬܐ ܝܢܐ؛ ܫܪܟܘܬܐ ܟܙܒܢܐ Dash Enterprise. ܨܘܪܬܐ interactive ܒܚܕ ܣܕܪܐ ܡܢ pandas. |
| Vega-Lite | ܓܪܡܛܝܩܐ ܓܪܦܝܬܐ declarative ܓܘ JSON ܩܐ ܨܘܪ̈ܬܐ interactive؛ ܫܬܐܣܐ ܕ-Altair ܓܘ Python. | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ / ܪܡܙܐ | ܢܘܣܚܐ 6.4 (2026). ܡܬܩܢܢܐ (editor) ܓܘ ܫܒܝܟܬܐ ܕܠܐ ܬܘܩܢܐ. |
| Observable | ܟܬ̈ܒܐ (notebooks) ܕ-JavaScript ܩܐ ܦܘܫܩܐ ܘ-visualization؛ Observable Plot ܘ-Framework – ܪܡܙܐ ܦܬܝܚܐ. | ܡܓܢ + ܒܦܪܥܢܐ | ܒܪܐܘܙܪ / ܪܡܙܐ | ܟܬ̈ܒܐ (notebooks) ܡܓܢ̈ܝܐ؛ Pro ܩܪܝܒ 22 ܕܘܠܪ̈ܐ ܒܝܪܚܐ. ܒܝܬܐ ܕܟܢܘܫܝܐ (community) ܕ-D3. |
| ggplot2 | ܨܪܪܐ ܕܓܪܦܝܩܐ ܕ-R ܠܦܘܬ "ܓܪܡܛܝܩܐ ܕܓܪܦܝܩܐ" – ܬܚܬܝ̈ܬܐ (layers)، aesthetics، panels. | ܪܡܙܐ ܦܬܝܚܐ | ܪܡܙܐ | ܢܘܣܚܐ 4.0 (2025). ܡܐܢܐ ܕܦܘܚܡܐ (reference) ܩܐ ܨܘܪ̈ܬܐ ܡܕܪ̈ܫܝܬܐ ܓܘ R؛ ܚܙܝܡܘܢ ܡܥܝܪܢܘܬܐ ܕܥܒܪܝܐ ܓܘ ܦܐܬܐ ܕܨܘܪܬܐ ܕܒܕܪܐ. |
ܡܥܝܪܢܘܬܐ. RAWGraphs ܘ-kepler.gl (ܠܘܚܐ 5) ܟܦܠܚܝ ܝܗܝ̈ܒܬܐ ܓܘ ܒܪܐܘܙܪ ܕܠܐ ܡܣܠܩܬܐ ܕܝܠܗܝܢ ܠܣܝܪܒܪ؛ Datawrapper ܘ-Flourish ܟܢܛܪܝ ܝܗܝ̈ܒܬܐ ܓܘ ܥܢܢܐ (cloud) ܕܝܠܗܘܢ – ܚܘܫܒܐ ܩܐ ܝܗܝ̈ܒܬܐ ܕܙܒܘ̈ܢܐ.
10. ܡܕܒܪܢܘܬܐ ܕܡܒܘ̈ܥܐ، ܝܕܥܬܐ ܦܬܝܚܬܐ ܘܫܘܬܦܘܬܐ
ܡܐܢ̈ܐ ܕܠܐ ܟܦܫܩܝ ܡܕܡ ܘܕܠܐ ܐܢܝ ܒܘܨܝܐ ܠܐ ܡܨܐ ܕܡܬܥܒܕ ܬܘܒ: ܡܕܒܪܢܘܬܐ ܕܪܫܝܡܬܐ ܕܡܒܘ̈ܥܐ (bibliography)، ܟܬܝܒܬܐ ܡܢ ܩܕܡ (preregistration)، ܡܕܒܪܢܘܬܐ ܕܢܘ̈ܣܚܐ (version control)، ܟܬܝܒܬܐ ܡܫܘܬܦܬܐ. ܬܪܝܢ ܫܪ̈ܫܐ ܕܝܕܥܬܐ ܦܬܝܚܬܐ ܐܣܝܪ̈ܐ ܝܢܐ ܬܪܝܨܐܝܬ ܥܡ ܐܗܐ ܣܐܝܛ: ܡܘܕܝܠ (model) ܕܟܬܝܒܐ ܝܠܗ ܡܢ ܩܕܡ ܡܬܬܢܝܐ ܝܠܗ ܒܐܘܪܚܐ ܐܚܪܬܐ ܡܢ ܡܘܕܝܠ ܕܫܚܠܦܠܗ ܒܬܪ ܗܕܐ (ܚܙܝܡܘܢ ܦܐܬܐ ܕܦܘܫܩܐ ܕܫܒ̈ܝܠܐ)، ܘܪܡܙܐ ܘܢܘܣܚܐ ܟܬܝܒ̈ܐ – ܐܝܟ ܕܟܠ ܦܐܬܐ ܓܘ ܣܐܝܛ ܛܥܢܐ ܡܢܝܢܐ ܕܢܘܣܚܐ.
ܫܪܫܐ ܩܕܡ ܡܐܢܐ. ܡܕܒܪܢܘܬܐ ܕܦܪܘܝܩܬ ܕܝܓܝܛܠܝܐ ܓܘ Drucker ܘ-Albrezzi (2026، ܦܐ̈ܬܐ 126-127): "ܫܘܪܝܐ ܒܡܕܡ ܕܡܨܝܚ ܕܥܒܕܚ"؛ ܒܢܝܢܐ ܥܡ ܡܨܝܐܘܬܐ ܕܦܬܝܘܬܐ ܐܠܐ ܕܠܐ ܬܠܝܘܬܐ ܒܢܛܪܬܐ ܕܟܠ ܐܡܢ؛ ܟܬܝܒܬܐ ܕܟܠ ܦܘܠܚܢܐ ܕܥܒܕܐ ܕܪܓܐ-ܕܪܓܐ، ܡܛܠ ܕܕܠܐ ܟܬܝܒܬܐ "ܐܦ ܕܥܪܬܐ ܠܥܒܕܐ ܕܝܠܘܟܘܢ ܡܨܝܐ ܕܗܘܝܐ ܥܣܩܬܐ"؛ ܡܐܢ̈ܐ ܕܪܡܙܐ ܦܬܝܚܐ ܥܡ ܟܢܘܫܝܐ ܪܒܐ ܕܡܦܠܚܢ̈ܐ "ܡܣܟܝ̈ܐ ܝܢܐ ܕܩܝܡܝ ܝܬܝܪ ܡܢ ܐܣܟܝ̈ܡܐ ܕܩܢܝܢܐ"؛ ܘܬܘܩܢܐ ܡܢ ܩܕܡ ܕ"ܚܝ̈ܐ ܕܒܬܪ" ܕܦܪܘܝܩܬ – "ܠܐ ܟܠ ܦܪܘܝܩܬ ܕܝܓܝܛܠܝܐ ܒܕ ܩܝܡ"، ܘ"ܙܒܢܐ ܕܚܫܒܬܐ ܕܟܝ ܒܕ ܡܦܩܚ ܬܚܘܡܐ ܕܡܕܥܐ ܓܘ ܫܘܪܝܐ ܝܠܗ". ܡܦܩܬܐ ܩܕܡܝܬܐ ܐܡܝܪܬܐ ܗܘܐ ܐܗܐ ܒܚܪܝܦܘܬܐ ܝܬܝܪ: "ܟܬܝܒܬܐ ܕܦܪܘܝܩܬ ܡܨܝܐ ܕܗܘܝܐ ܬܘܣܦܬܐ ܛܒܬܐ ܡܢ ܟܠ" (Drucker, 2021, Section 12a). ܘܥܠ ܐܬܪ̈ܘܬܐ (platforms) (ܦܐܬܐ 110): "ܟܠ ܐܡܢ ܒܚܘܪܘܢ function ܕܡܦܩܬܐ (export)" – ܬܚܘܡܐ ܕܒܢܝܐ ܝܠܗ ܓܘ ܬܘܟܢܝܬܐ ܕܚܘܝܐ ܕܠܐ ܟܡܦܩܐ ܥܒܕܐ ܐܒܝܕܐ ܝܠܗ؛ ܛܘ̈ܦܣܐ ܩܐ ܫܘܬܦܘܬܐ ܕܝܗܝ̈ܒܬܐ (LoD، IIIF، CIDOC-CRM) ܡܘܬܪ̈ܢܐ ܝܢܐ، ܐܠܐ ܝܩܝܪ̈ܐ ܝܢܐ ܩܐ ܡܦܠܚܢܘܬܐ ܘܡܛܠ ܗܕܐ ܟܓܒܝ ܡܕܪ̈ܫܝܬܐ ܥܬܝܪ̈ܬܐ (ܦܐܬܐ 114). ܐܝܬܝܩܐ ܘܢܡܘܣܐ (ܦܐ̈ܬܐ 128-129): ܕܝܓܝܛܠܝܐ ܟܦܫܩ ܢܣܚܐ، ܘܡܛܠ ܗܕܐ ܣܢܝܩ ܝܠܗ ܠܣܘܟܠܐ ܕܙܕܩ̈ܐ ܕܟܬܒܢܘܬܐ (copyright)، ܡܦܠܚܢܘܬܐ ܟܐܢܬܐ (fair use) ܘܐܦܣܢܘ̈ܝܬܐ ܕ-Creative Commons؛ "ܡܝܬܝܬܐ ܓܢܒܐ ܣܢܝܩܐ ܝܠܗ ܕܒܘܨܝܐ ܘܣܢܝܩ ܝܠܗ ܕܥܒܕܚ ܠܗ̇ ܓܘ ܟܠ ܐܝܟܢܝ̈ܘܬܐ"؛ ܐܣܘܪܐ (link) ܠܐ ܟܒܥܐ ܐܦܣܢܘܬܐ، ܘܡܨܝܚ ܕܡܚܘܚ ܚܘܡܪܐ ܓܘ ܟܘܬܐ (window) ܕܠܐ ܢܛܪܬܐ ܕܝܠܗ ܓܘ ܣܝܪܒܪ ܕܝܠܘܟܘܢ؛ ܘܢܡܘܣܐ ܕܕܗܒܐ – "ܚܫܘܒܘܢ ܠܥܒܕܐ ܕܐܚܪ̈ܢܐ ܐܝܟ ܕܒܥܝܬܘܢ ܗܘܐ ܕܚܫܒܝ ܠܥܒܕܐ ܕܝܠܘܟܘܢ".
ܠܘܚܐ 10. ܡܕܒܪܢܘܬܐ ܕܡܒܘ̈ܥܐ، ܝܕܥܬܐ ܦܬܝܚܬܐ ܘܫܘܬܦܘܬܐ
| ܡܐܢܐ | ܡܘܕܝ ܟܥܒܕ | ܐܦܣܢܘܬܐ ܘܛܝܡܐ | ܡܨܥܬܐ | ܡܥܝܪ̈ܢܘܬܐ (notes) |
|---|---|---|---|---|
| Zotero | ܡܕܒܪܢܐ ܕܪܫܝܡܬܐ ܕܡܒܘ̈ܥܐ (bibliography) ܡܓܢ: ܟܢܫܐ ܒܚܕ ܕܚܩܐ ܡܢ ܒܪܐܘܙܪ، ܪܘܫܡܐ (tagging)، ܡܥܝܪ̈ܢܘܬܐ ܥܠ PDF، ܡܝܬܝܬܐ ܓܘ Word ܒܟܠ ܐܣܟܝܡܐ. | ܪܡܙܐ ܦܬܝܚܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܒܪܐܘܙܪ | ܢܘܣܚܐ 10 (2026)؛ ܫܘܬܦܘܬܐ (non-profit) Digital Scholar. 300MB ܕܐܚܕܘܬܐ (sync) ܡܓܢ. ܐܣܟܝܡܐ APA 7 ܒܢܝܐ ܓܘܗ؛ ܟܡܣܡܟ ܥܒܪܝܐ ܘ-RTL ܒܫܪܪܐ. |
| Mendeley | ܡܕܒܪܢܐ ܕܪܫܝܡܬܐ ܕܡܒܘ̈ܥܐ ܕ-Elsevier ܥܡ ܡܥܝܪ̈ܢܘܬܐ ܕ-PDF، ܬܘܣܦܬܐ ܕ-Word ܘܐܚܕܘܬܐ (sync). | ܡܓܢ + ܒܦܪܥܢܐ | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ / ܒܪܐܘܙܪ | ܢܘܣܚܐ Desktop ܥܬܝܩܐ ܦܝܫܠܗ ܒܚܝ̈ܐ (2025) ܒܬܪ ܬܘܩܢܐ ܕܒܛܠܬܐ. ܡܓܢ؛ ܢܛܪܬܐ ܝܬܝܪܬܐ ܒܦܪܥܢܐ. |
| OSF | ܐܬܪܐ (platform) ܡܓܢ ܩܐ ܟܬܝܒܬܐ ܡܢ ܩܕܡ (preregistration)، ܢܘ̈ܣܚܐ ܩܕܡ̈ܝܐ (preprints)، ܫܘܬܦܘܬܐ ܕܝܗܝ̈ܒܬܐ ܘܡܕܒܪܢܘܬܐ ܕܦܪܘܝܩܬ. | ܪܡܙܐ ܦܬܝܚܐ | ܒܪܐܘܙܪ | Center for Open Science. ܟܬܝܒܬܐ ܡܢ ܩܕܡ ܟܩܒܠܐ ܛܒܥܐ ܕܙܒܢܐ (timestamp) ܘ-DOI. ܟܡܬܚܠܛ ܥܡ GitHub، Dropbox، Zenodo. |
| GitHub | ܡܕܒܪܢܘܬܐ ܕܢܘ̈ܣܚܐ (git)، ܫܘܬܦܘܬܐ ܕܪܡܙܐ، ܣܐܝ̈ܛܐ ܕ-GitHub Pages – ܕܘܟܬܐ ܕܡܬܬܩܢܬܐ ܝܠܗ̇ ܩܐ ܐܗܐ ܣܐܝܛ. | ܡܓܢ + ܒܦܪܥܢܐ | ܒܪܐܘܙܪ / ܪܡܙܐ | ܡܓܢ ܩܐ ܓܙ̈ܐ (repositories) ܕܥܡܐ ܘܝܚܝ̈ܕܝܐ؛ GitHub Education ܩܐ ܬܠܡܝ̈ܕܐ ܘܩܐ ܡܠܦ̈ܢܐ. Microsoft. |
| Overleaf | ܡܬܩܢܢܐ (editor) ܕ-LaTeX ܕܫܘܬܦܘܬܐ ܓܘ ܒܪܐܘܙܪ، ܥܡ ܛܘ̈ܦܣܐ (templates) ܕܟܬ̈ܒܐ ܙܒ̈ܢܝܐ (journals). | ܡܓܢ + ܒܦܪܥܢܐ | ܒܪܐܘܙܪ | ܡܓܢ ܩܐ ܦܪܘܝ̈ܩܬܐ ܥܡ ܚܕ ܫܘܬܦܐ؛ ܡܕܪ̈ܫܝܬܐ ܥܠܝ̈ܬܐ ܣܓܝ̈ܐܐ ܐܝܬ ܠܗܝ̇ ܐܦܣܢܘܬܐ. ܥܒܪܝܐ – ܒܝܕ ܨܪ̈ܪܐ ܕ-LaTeX (polyglossia). |
| Hypothes.is | ܬܚܬܝܬܐ ܕܡܥܝܪ̈ܢܘܬܐ ܕܫܘܬܦܘܬܐ ܥܠ ܟܠ ܦܐܬܐ ܕܐܢܛܪܢܝܬ ܘ-PDF، ܥܡ ܓܘ̈ܕܐ ܝܚܝ̈ܕܝܬܐ. | ܡܓܢ + ܒܦܪܥܢܐ | ܒܪܐܘܙܪ | ܠܒܐ (core) ܪܡܙܐ ܦܬܝܚܐ ܝܠܗ؛ ܡܓܢ ܩܐ ܝܚܝ̈ܕܝܐ. ܩܐ ܩܪܝܢܐ ܡܫܘܬܦܐ ܕܣܡܝܢܪ ܝܢ ܕܓܘܕܐ ܕܒܘܨܝܐ. |
| Obsidian | ܪܫܝܡ̈ܬܐ (notes) ܕ-Markdown ܐܬܪ̈ܢܝܬܐ ܥܡ ܐܣܘܪ̈ܐ ܕܬܪܝܢ ܐܘܪ̈ܚܬܐ، ܚܘܝܐ ܕ-graph ܘܬܘܣܦ̈ܬܐ (plugins). | ܡܓܢ (ܩܦܝܠܐ) | ܬܘܟܢܝܬܐ ܩܐ ܬܘܩܢܐ | ܦܐܝ̈ܠܐ ܥܠ ܚܘܫܒܢܐ ܕܝܘܟܘܢ، ܒܡ̈ܠܐ ܦܫܝ̈ܛܐ. ܡܓܢ ܐܦ ܩܐ ܡܦܠܚܢܘܬܐ ܬܓܪܝܬܐ (2025)؛ ܐܚܕܘܬܐ (sync) – ܒܦܪܥܢܐ. ܥܘܕܪܢܐ ܕ-RTL ܓܘ ܬܘܩ̈ܢܐ (settings). |
| Connected Papers | graph ܕܕܡܝܘܬܐ ܕܡܐܡܪ̈ܐ ܚܕܪ ܡܐܡܪܐ ܕܫܘܪܝܐ، ܩܐ ܨܘܪܬܐ ܕܟܬܒ̈ܐ (literature mapping). | ܡܓܢ + ܒܦܪܥܢܐ | ܒܪܐܘܙܪ | 5 graphs ܒܝܪܚܐ ܡܓܢ. ܡܫܠܡܢܐ ܠܒܨܝܐ ܕܡ̈ܠܐ ܪ̈ܫܝܬܐ (keywords) – ܟܡܫܟܚ ܡܐ ܕܠܝܬ ܠܗ ܡ̈ܠܐ ܕܝܠܘܟܘܢ. |
| ResearchRabbit | ܨܘܪ̈ܬܐ ܕܟܬܒ̈ܐ (literature maps) ܣܡܝܟ̈ܐ ܥܠ ܡܨܝܕܬܐ ܕܡܬ̈ܝܬܐ، ܥܡ ܡܥܗܕ̈ܢܘܬܐ ܥܠ ܡܐܡܪ̈ܐ ܚܕ̈ܬܐ. | ܡܓܢ (ܩܦܝܠܐ) | ܒܪܐܘܙܪ | ܡܓܢ (ܐܝܬ ܦܐܬܐ ܕܛܝ̈ܡܐ – ܒܚܘܪܘܢ). ܟܡܬܐܚܕ (sync) ܥܡ Zotero. |
ܡܥܝܪܢܘܬܐ. Zotero ܝܚܝܕܝܐ ܝܠܗ ܠܐܟܐ ܕܐܦ ܪܡܙܐ ܦܬܝܚܐ ܝܠܗ ܘܐܦ ܡܬܕܒܪܐ ܝܠܗ ܒܝܕ ܫܘܬܦܘܬܐ (non-profit)؛ Mendeley (Elsevier)، Overleaf (Digital Science) ܘ-GitHub (Microsoft) – ܬܓܪ̈ܝܐ ܝܢܐ ܥܡ ܬܘܩܢܐ ܡܓܢ.
ܛܥܝ̈ܘܬܐ ܕܡܬܚܙܝܢ ܣܓܝ (Common mistakes)
ܓܘܒܝܐ ܕܡܐܢܐ ܩܕܡ ܫܘܐܠܐ. ܛܥܝܘܬܐ ܩܕܡܝܬܐ ܘܕܡܬܚܙܝܐ ܝܬܝܪ: "ܐܝܬ ܠܝ corpus، ܬܐ ܕܥܒܕܚ topic modeling". topic modeling ܟܦܢܐ ܥܠ ܫܘܐܠܐ ܦܪܝܫܐ (ܐܝܢܝ ܟܢܘ̈ܫܝܐ ܕܡ̈ܠܐ ܟܕܥܪܝ ܐܟܚܕܐ) ܘܠܐ ܥܠ ܐܚܪ̈ܢܐ (ܡܢܘ ܐܡܪܠܗ ܡܘܕܝ ܠܡܢܘ). ܩܕܡ ܟܠ ܡܕܡ ܫܘܐܠܐ، ܒܬܪ ܗܕܐ ܙܢܐ ܕܝܗܝ̈ܒܬܐ ܕܟܦܢܐ ܥܠܗ، ܘܒܣ ܒܬܪ ܗܕܐ ܡܐܢܐ – ܐܗܐ ܝܠܗ ܐܦ ܛܟܣܐ ܕܥܡܘ̈ܕܐ ܓܘ ܪܫܝܡܬܐ ܕܒܘܚܪܢܐ ܕܠܬܚܬ.
ܫܕܪܬܐ ܕܝܗܝ̈ܒܬܐ ܪܓܝܫ̈ܬܐ ܠܣܝܪܒܪ ܕܠܐ ܚܘܪܐ. ܡܫܐܠܬܐ ܕܡܕܒܩܬܐ ܝܠܗ̇ ܓܘ Voyant، ܦܐܝܠ ܕܒܘܨܝܐ ܕܫܘܐ̈ܠܐ ܕܡܣܠܩܐ ܝܠܗ ܠ-Flourish – ܠܐ ܝܢܐ ܬܘܒ ܥܠ ܚܘܫܒܢܐ ܕܝܘܟܘܢ. ܫܘܪܪܐ ܕܓܘܕܐ ܕܐܝܬܝܩܐ ܕܩܒܠܠܘܟܘܢ ܟܬܝܒܠܗ، ܩܪܝܒܐܝܬ ܒܫܪܪܐ، ܡܕܡ ܐܚܪܢܐ.
ܬܘܟܠܢܐ ܥܠ tokenization ܕܥܒܪܝܐ. ܡܐܢܐ ܕܟܦܪܩ "וכשהלכנו" ܠܚܕܐ ܡܠܬܐ ܒܕ ܒܢܐ ܣܛܐܛܝܣܛܝܩܐ ܛܥܝܬܐ ܒܫܠܝܐ – ܣܓܝܐܘ̈ܬܐ (frequencies) ܕ"הלך" ܒܕ ܛܫܝ ܓܘ ܐܠܦ̈ܐ ܕܐܣܟܝ̈ܡܐ. ܩܐ ܥܒܪܝܐ – ܦܘܪܩܐ ܡܘܪܦܘܠܘܓܝܐ ܩܕܡ ܟܠ ܡܢܝܢܐ (ܠܘܚܐ 3).
ܒܢܝܢܐ ܕܦܪܘܝܩܬ ܥܠ ܡܐܢܐ ܕܠܐ ܡܬܦܬܚ. Palladio، YAP، GRETIL – ܦܥܠ̈ܐ ܝܢܐ، ܐܠܐ ܚܘܕܬܐ ܐܚܪܝܬܐ ܩܕܡ ܫܢ̈ܐ ܝܠܗ̇. ܡܐܢܐ ܐܝܟ ܐܗܐ ܛܒܐ ܝܠܗ ܩܐ ܒܘܨܝܐ؛ ܩܐ ܦܪܘܝܩܬ ܕܬܪܬܝܢ ܫܢ̈ܐ – ܒܚܘܪܘܢ ܡܦܩܬܐ (export) ܠܐܣܟܝܡܐ ܦܬܝܚܐ (CSV, GraphML, TEI) ܗܕܟܐ ܕܥܒܕܐ ܩܐܝܡ ܒܬܪ ܡܐܢܐ.
scraping ܕܠܐ ܫܘܐܠܐ. ܫܪ̈ܛܐ ܕܡܦܠܚܢܘܬܐ (Terms of use) ܕܐܬܪܐ، ܓܢܝܙܘܬܐ (privacy) ܕܡܦܠܚܢ̈ܐ ܘܢܡܘܣܐ ܐܬܪܢܝܐ ܩܕܡ ܣܕܪܐ ܩܕܡܝܐ ܕܪܡܙܐ ܝܢܐ. Salganik (2018، ܦܐ̈ܬܐ 294-299) ܟܡܩܪܒ ܛܘܦܣܐ ܕܐܪܒܥܐ ܫܪ̈ܫܐ – ܐܝܩܪܐ ܠܐܢܫܐ، ܝܘܬܪܢܐ، ܟܐܢܘܬܐ، ܐܝܩܪܐ ܠܢܡܘܣܐ ܘܠܛܒܬܐ ܕܥܡܐ – ܘܩܐ ܡܘܕܝ ܫܠܡܘܬܐ ܡܢ ܝܕܥܬܐ (informed consent) ܠܐܟܐ ܦܪܝܫܬܐ ܝܠܗ̇ ܡܢ ܢܣܝܘܢܐ ܕܡܥܒܕܬܐ (ܦܐ̈ܬܐ 303-306).
ܬܗܪܐ ܡܢ ܪܒܘܬܐ. ܡܠܝܘܢ ܪ̈ܘܫܡܐ (records) ܡܢ ܚܕ ܐܬܪܐ ܕܘܡܝܐ (sample) ܝܢܐ ܕܠܐ ܕܡܐ ܠܡܦܠܚܢ̈ܐ ܕܐܬܪܐ، ܕܥܘܒܕܐ ܕܝܠܗܘܢ "ܡܬܕܒܪܐ ܝܠܗ ܒܝܕ ܢܝܫ̈ܐ ܕܗܢܕܣܐ ܕܛܟܣܐ" – ܘܠܐ ܠܟܢܫܐ ܟܠܢܝܐ (population)؛ "ܛܘ̈ܦܣܐ ܕܝܗܝ̈ܒܬܐ ܪ̈ܒܐ ܐܘܪܚܐ ܝܢܐ ܠܢܝܫܐ، ܠܐ ܢܝܫܐ ܒܢܦܫܗ" (Salganik, 2018, pp. 17, 29, 35). ܫܘܐܠܐ ܠܐ ܝܠܗ ܟܡܐ، ܐܠܐ ܡܢܘ، ܘܡܘܕܝ ܥܒܕܠܗ ܛܟܣܐ ܠܗܘܢ.
simulation ܕܠܐ verification ܘ-validation. ܡܘܕܝܠ (model) ܕܟܪܗܛ ܘܟܥܒܕ ܨܘܪܬܐ ܠܐ ܝܠܗ ܡܫܟܚܢܘܬܐ: ܩܕܡ ܟܠ ܡܕܡ verification – ܕܪܡܙܐ ܟܥܒܕ ܡܐ ܕܡܘܕܝܠ ܕܚܘܫܒܐ ܟܐܡܪ ("ܡܘܕܝܠ ܕܠܐ ܡܫܪܪܐ ܝܠܗ ܠܐ ܦܐܝܐ ܝܠܗ ܩܐ ܦܘܫܩܐ") – ܘܒܬܪ ܗܕܐ validation ܩܘܒܠ ܝܗܝ̈ܒܬܐ ܢܣܝܢ̈ܝܬܐ؛ ܘܬܪܘܝܗܝ ܬܘܒ ܠܐ ܣܦܩܝ ܩܐ ܕܝܢܐ ܕܐܝܟܝܘܬܐ (Cioffi-Revilla, 2017, pp. 388-393). ܘܪܡܙܐ ܕ-simulation "ܟܡܬܚܒܠ" – ܕܠܐ ܟܬܝܒܬܐ ܘܓܙܐ (CoMSES) ܐܗܘ ܟܛܫܐ.
ܠܐ ܟܬܝܒܬܐ ܕܢܘܣܚܐ ܘܕܦܪ̈ܡܝܛܪܐ. topic modeling ܥܡ k = 20 ܘ-k = 40 ܟܝܗܒ ܬܪܝܢ ܒܘܨ̈ܝܐ ܦܪ̈ܝܫܐ؛ Gephi ܥܡ ܦܘܪܣܐ (layout) ܐܚܪܢܐ ܟܝܗܒ ܬܪܬܝܢ ܨܘܪ̈ܬܐ ܦܪ̈ܝܫܬܐ. ܦܐܪܐ ܚܘܫܒܢܝܐ ܕܠܐ ܟܬܝܒܐ ܝܠܗ ܗܠ ܕܪܓܐ ܕܢܘܣܚܐ ܘܕܦܪܡܝܛܪ ܠܐ ܡܨܐ ܕܡܬܥܒܕ ܬܘܒ – ܘܡܛܠ ܗܕܐ ܠܐ ܝܠܗ ܡܫܟܚܢܘܬܐ.
ܚܘܠܛܐ ܕܡܢܒܝܢܘܬܐ (prediction) ܥܡ ܦܘܫܩܐ. ܡܘܕܝܠ ܕܝܘܠܦܢܐ ܕܡܟܝܢܐ ܕܡܢܒܐ ܫܦܝܪ 92% ܠܐ ܟܡܦܫܩ ܡܕܡ ܥܠ ܥܠܬܐ، ܘܡܢܝܢܐ ܡܫܘܬܦܐ (coefficient) ܕܪܝܓܪܫܢ ܪܫܝܡܐ ܠܐ ܟܡܫܪܪ ܡܢܒܝܢܘܬܐ ܛܒܬܐ. ܬܪܝܢ ܢܝܫ̈ܐ، ܬܪܝܢ ܒܘܚܪ̈ܢܐ ܕܬܪܝܨܘܬܐ (validity).
ܩܪܝܢܐ ܠܝܗܝ̈ܒܬܐ "ܝܗܝ̈ܒܬܐ". ܡܐ ܕܟܥܐܠ ܠܡܐܢܐ ܫܩܝܠܐ ܝܠܗ ܡܢ ܚܘܡܪܐ ܒܦܣ̈ܩܬܐ – ܡܘܢܐ ܝܠܗ̇ ܚܕܝܘܬܐ، ܡܘܕܝ ܡܢܝܐ ܝܠܗ، ܡܘܕܝ ܫܕܝܐ ܝܠܗ – ܘ-Drucker ܘ-Albrezzi (2026، ܦܐܬܐ 15) ܟܡܩܪܒܝ ܕܩܪܝܚ ܠܗ capta. ܛܥܝܘܬܐ ܠܐ ܝܠܗ̇ ܓܘ ܡܠܬܐ ܐܠܐ ܓܘ ܡܐ ܕܟܡܛܫܝܐ: ܡܘܕܝܠ ܕܝܗܝ̈ܒܬܐ ܕܠܐ ܟܬܝܒܐ ܝܠܗ ܦܘܫܩܐ ܝܠܗ ܕܠܐ ܡܘܕܥܐ ܝܠܗ.
ܬܘܟܠܢܐ ܥܠ ܦܬܝܘܬܐ ܕܐܦܐ ܘܥܠ ܣܪܛܐ. ܚܘܕܪܐ ܕܛܝܡܐ ܕܝܠܗ ܥܦܝܦܐ ܘܦܬܝܘܬܐ ܕܝܠܗ ܐܪܒܥܐ ܐܥܦ̈ܐ؛ ܣܪܛܐ ܕܐܣܪ ܓܢ̈ܣܐ ܐܝܟ ܕܣܕܪܐ ܝܢܐ؛ ܣܒܠܬܐ (scale) ܕܚܕ ܛܝܡܐ ܢܘܟܪܝܐ ܡܬܚܠܗ̇. Drucker ܘ-Albrezzi (2026، ܦܐܬܐ 67): "ܟܠ visualizations ܦܘܫ̈ܩܐ ܝܢܐ، ܠܐ ܚܘ̈ܝܐ ܕܥܒ̈ܕܐ" – ܘܡܢܬܐ ܡܢ ܕܝܠܝ̈ܬܐ ܓܪܦ̈ܝܬܐ ܦܐܪ̈ܐ ܝܢܐ ܕܚܘܝܐ، ܠܐ ܕܝܗܝ̈ܒܬܐ.
ܡܝܬܝܬܐ ܕܡܐ ܕܡܘܕܝܠ ܕܠܫܢܐ "ܐܫܟܚܠܗ". ܡܘܕܝܠ ܟܠܢܝܐ ܕܠܫܢܐ ܟܦܢܐ ܐܦ ܐܝܡܢ ܕܠܝܬ ܠܗ ܡܒܘܥܐ، ܘܡܐ ܕܠܐ ܝܠܗ ܓܘ ܛܘܦܣܐ ܕܝܘܠܦܢܐ (training set) ܕܝܠܗ ܟܡܬܚܙܐ ܐܝܟ ܕܠܝܬ – "ܘܓܒ ܙܒ̈ܢܐ، ܐܝܡܢ ܕܐܗܐ ܟܗܘܐ، ܛܟܣܐ ܟܡܢܣܐ ܕܒܢܐ ܝܕܥܬܐ ܕܒܥܝܬܐ ܝܠܗ̇"؛ ܡܒܘܥܐ ܕܝܗܝ̈ܒܬܐ (provenance) ܕܪܘܒܐ ܕܡܘܕܝ̈ܠܐ ܐܘܟܡܐ ܝܠܗ، ܘܐܢ ܠܐ ܝܠܗ ܛܟܣܐ ܕ-RAG ܠܐ ܝܕܥܚ ܥܠ ܡܘܕܝ ܣܡܝܟܐ ܝܠܗ ܡܦܩܢܐ (Drucker & Albrezzi, 2026, pp. 119, 121). ܡܦܩܢܐ (output) ܕܡܘܕܝܠ ܢܘܩܙܐ ܕܫܘܪܝܐ ܝܠܗ ܩܐ ܒܘܚܪܢܐ ܩܘܒܠ ܡܒܘܥܐ – ܠܐ ܡܒܘܥܐ.
ܣܒܪܐ ܕܡܨܝܕܬܐ ܓܡܝܪܬܐ ܝܠܗ̇. ܡܚܘ̈ܝܢܐ ܕܡܨܥܝܘܬܐ (centrality) ܘܕܪܘܚܩܐ ܚܫܝܒ̈ܐ ܝܢܐ ܥܠ ܡܐ ܕܟܢܝܫܐ ܝܠܗ؛ ܚܕ ܐܣܘܪܐ ܚܣܝܪܐ ܡܨܐ ܕܥܒܕ "ܓܫܪܐ" "ܚܘܪܐ ܕܒܢܝܢܐ" (structural hole). Dawson (2020، ܦܐ̈ܬܐ 356-361): ܙܕܩܐ ܕܬܚܘܡܐ ܕܡܨܝܕܬܐ، ܘܐܡܪܬܐ ܡܘܕܝ ܚܣܝܪܐ ܝܠܗ.
ܪܫܝܡܬܐ ܕܒܘܚܪܢܐ – ܩܕܡ ܕܫܪܝܚ ܥܡ ܡܐܢܐ ܚܕܬܐ
| ܫܘܐܠܐ | ܩܡܘܕܝ ܐܗܐ ܚܫܝܚܐ ܝܠܗ |
|---|---|
| ܡܘܢܐ ܝܠܗ ܫܘܐܠܐ، ܘܐܝܢܐ ܙܢܐ ܕܝܗܝ̈ܒܬܐ ܟܦܢܐ ܥܠܗ؟ | ܡܐܢܐ ܢܦܩ ܡܢ ܝܗܝ̈ܒܬܐ، ܠܐ ܗܦܘܟܐ. |
| ܠܐܝܟܐ ܟܐܙܠܝ ܝܗܝ̈ܒܬܐ – ܚܘܫܒܢܐ، ܣܝܪܒܪ ܕܡܕܪܫܬܐ ܝܢ ܥܢܢܐ (cloud) ܬܓܪܝܐ؟ | ܢܛܘܪܘܬܐ ܕܐܪ̈ܙܐ (confidentiality)، ܐܝܬܝܩܐ، ܘܫܘܪܪܐ ܕܓܘܕܐ. |
| ܡܘܕܝ ܟܗܘܐ ܠܥܒܪܝܐ ܓܘ ܡܐܢܐ – ܒܣ tokenization، ܝܢ ܦܘܪܩܐ ܡܘܪܦܘܠܘܓܝܐ؟ | ܟܠ ܡܢܝܢܐ ܛܥܝܐ ܒܕܪܓܐ ܕܡܠܬܐ ܟܡܬܝܪܬ ܠܥܠ. |
| ܡܘܕܝ ܝܠܗ̇ ܐܝܟܢܝܘܬܐ ܕܡܦܬܚܢܘܬܐ؟ ܐܝܡܢ ܝܠܗ ܢܘܣܚܐ ܐܚܪܝܐ؟ | ܡܐܢܐ ܫܒܝܩܐ = ܣܘܟܢܐ ܩܐ ܦܪܘܝܩܬ ܐܪܝܟܐ. |
| ܠܐܝܢܐ ܐܣܟܝܡܐ ܦܬܝܚܐ ܡܨܝܚ ܕܡܦܩܚ (export)؟ | CSV، TEI، GraphML، GeoJSON – ܥܒܕܐ ܟܩܐܝܡ ܒܬܪ ܡܐܢܐ. |
| ܟܬܝܒܠܝ ܢܘܣܚܐ، ܦܪ̈ܡܝܛܪܐ ܘܪܡܙܐ؟ | ܬܘܪܨܐ ܕܦܐܪ̈ܐ (reproducibility). ܕܠܐ ܐܗܐ – ܠܝܬ ܡܫܟܚܢܘܬܐ. |
| ܒܚܪܠܝ ܕܘܡܝܐ (sample) ܒܐܝܕܐ ܩܘܒܠ ܡܦܩܢܐ (output) ܕܒܚܘܕܝܗ؟ | ܗܘ ܫܪܫܐ ܕܐܗܐ ܣܐܝܛ – ܨܠܝܒܘܬܐ (cross-check) ܡܢܝܢܐ-ܒܡܢܝܢܐ. |
| ܟܬܝܒܠܝ ܡܘܕܝܠ (model) ܕܝܗܝ̈ܒܬܐ – ܡܘܢܐ ܝܠܗ̇ ܚܕܝܘܬܐ، ܡܘܕܝ ܡܢܝܐ ܝܠܗ، ܡܘܕܝ ܫܩܝܠܐ ܝܠܗ؟ | ܝܗܝ̈ܒܬܐ "ܫܩܝܠ̈ܬܐ" ܝܢܐ، ܠܐ "ܝܗܝ̈ܒܬܐ" (Drucker & Albrezzi, 2026, pp. 15, 18)؛ ܕܠܐ ܟܬܝܒܬܐ ܕܡܘܕܝܠ، ܦܘܫܩܐ ܟܣܝܐ ܝܠܗ. |
| ܦܐܪܐ ܟܕܥܪ ܐܝܟ ܕܐܝܬܘܗܝ ܓܘ ܪܗܛܐ ܡܬܢܝܐ، ܥܡ ܗܘ ܙܪܥܐ (random seed) ܘܗܘ ܢܘܣܚܐ؟ | ܚܦܪܬܐ ܕܡ̈ܠܐ ܘ-topic modeling "ܟܕܥܪܝ ܦܐܪ̈ܐ ܕܙܝܥܠܗܘܢ" (Drucker & Albrezzi, 2026, p. 54) – ܙܪܥܐ، ܢܘܣܚܐ ܘܦܪ̈ܡܝܛܪܐ ܡܢܬܐ ܝܢܐ ܡܢ ܡܫܟܚܢܘܬܐ. |
| ܐܝܬ ܓܘ ܝܗܝ̈ܒܬܐ ܝܕܥܬܐ ܝܚܝܕܝܬܐ – ܡܘܢܥܐ ܕ-IP، ܫܡܐ ܕܡܦܠܚܢܐ، ܕܘܟܬܐ – ܘܠܡܢܘ ܐܝܬ ܙܕܩܐ ܥܠܝܗܝ؟ | ܝܗܝ̈ܒܬܐ ܝܚܝ̈ܕܝܬܐ ܠܦܘܬ GDPR ܘܢܡܘܣܐ ܕܢܛܪܬܐ ܕܓܢܝܙܘܬܐ (Privacy Protection Law)؛ "ܙܕܩܐ ܕܓܙܐ ܕܝܗܝ̈ܒܬܐ" ܘܐܦܣܢܘܬܐ ܕܚܘܡܪܐ (Dawson, 2020, pp. 79-85, 188-193; Drucker & Albrezzi, 2026, pp. 128-129). |
| ܐܢ ܡܦܠܚܠܝ ܒܡܘܕܝܠ ܕܠܫܢܐ – ܐܗܘ ܦܬܝܚܐ ܝܢ ܩܦܝܠܐ ܝܠܗ، ܐܝܟܐ ܦܘܠܚ̈ܐ ܗܘܘ ܝܗܝ̈ܒܬܐ، ܘܡܘܕܝ ܟܐܡܪܝ ܫܪ̈ܛܐ ܕܡܦܠܚܢܘܬܐ (Terms of use) ܥܠ prompts ܕܝܝ؟ | ܡܘܕܝܠ ܩܦܝܠܐ ܟܦܠܚ ܥܠ ܣܝܪܒܪ ܕܩܢܝܢܐ ܘܓܒ ܙܒ̈ܢܐ ܟܡܠܦ ܥܠ prompts؛ ܡܘܕܝܠ ܦܬܝܚܐ ܐܬܪܢܝܐ، ܝܢ RAG ܥܠ ܓܙܐ ܡܚܕܕܐ – ܩܐ ܝܗܝ̈ܒܬܐ ܪܓܝܫ̈ܬܐ (Drucker & Albrezzi, 2026, pp. 118-119, 121). |
| ܐܢ ܝܗܝ̈ܒܬܐ "ܡܛܝܒ̈ܬܐ ܡܢ ܩܕܡ" ܝܢܐ – ܡܢܘ ܒܢܝܠܗ ܠܗܝ̇، ܩܐ ܡܘܕܝ، ܘܡܘܕܝ ܥܒܕܠܗ ܛܟܣܐ ܠܥܘܒܕܐ ܕܟܬܝܒܐ ܝܠܗ؟ | ܥܣܪܐ ܕܝܠܝ̈ܬܐ ܕ-Salganik: ܠܐ ܓܡܝܪ̈ܐ، ܠܐ ܕܡܝ̈ܐ ܠܟܢܫܐ ܟܠܢܝܐ، ܕܙܝܥܝ، ܡܚܠܛ̈ܐ ܒܝܕ ܐܠܓܘܪܝܬܡ̈ܐ (Salganik, 2018, pp. 17-41) – ܬܚܘ̈ܡܐ ܕܟܟܬܒܚ ܓܠܝܐܝܬ. |
| ܓܘ simulation – ܥܒܕܠܝ verification (ܪܡܙܐ ܟܥܒܕ ܡܐ ܕܡܬܬܩܢܐ ܗܘܐ) ܘܐܦ validation (ܡܦܩܢܐ ܦܐܐ ܠܝܗܝ̈ܒܬܐ)، ܘܟܬܝܒܠܝ ܬܪܘܝܗܝ؟ | verification = ܬܪܝܨܘܬܐ (validity) ܓܘܝܬܐ؛ validation = ܦܐܝܘܬܐ ܕܛܘ̈ܦܣܐ ܥܡ ܝܗܝ̈ܒܬܐ ܢܣܝܢ̈ܝܬܐ؛ ܪܡܙܐ ܕ-simulation ܟܡܬܚܒܠ (Cioffi-Revilla, 2017, pp. 388-390). |
| ܐܝܬ ܚܕ ܓܘ ܡܨܝܕܬܐ، ܓܘ ܨܘܪܬܐ ܕܐܬܪܐ ܝܢ ܓܘ ܡܘܕܝܠ ܕܡܨܐ ܕܩܒܠ ܚܒܠܐ ܡܢ ܡܦܪܣܡܢܘܬܐ؟ | ܠܐ ܝܕܝܥܘܬܐ (anonymity) ܟܬܒܪܐ ܡܢ ܕܘܟܬܐ ܓܘ ܡܨܝܕܬܐ؛ ܡܘܕܝܠ ܡܨܐ ܕܪܫܡ ܦܪ̈ܨܘܦܐ ܩܐ ܥܒܕܐ (Dawson, 2020, pp. 4-9, 356-361). |
| ܩܐ ܒܘܚܪܢܐ ܕܣܢܝܩܬܐ ܝܘܢ ܠܗ، ܡܢ ܩܕܡ ܐܝܬ ܡܚܫܒܢܐ (calculator) ܓܘ ܣܐܝܛ؟ | ܐܢ ܐܝܢ – ܐܗܘ ܝܠܗ ܡܐܢܐ: ܓܘ ܒܪܐܘܙܪ، ܕܠܐ ܫܕܪܬܐ ܕܝܗܝ̈ܒܬܐ، ܥܡ ܬܘܢܝܐ ܕ-APA. |
ܘܡܘܕܝ ܐܝܬ ܠܐܟܐ، ܓܘ ܣܐܝܛ
ܦܐ̈ܬܐ ܕܡܚܫܒ̈ܢܐ ܕܦܪܘܦܣܘܪ ܣܛܐܛ ܟܟܣܝ ܬܚܬܝܬܐ ܕܣܛܐܛܝܣܛܝܩܐ ܕܪܘܒܐ ܕܒܘܨ̈ܝܐ ܕܓܘ ܬܪܝܢ ܚܩ̈ܠܐ – ܓܘ ܒܪܐܘܙܪ، ܕܠܐ ܕܝܗܝ̈ܒܬܐ ܫܒܩܝ ܚܘܫܒܢܐ، ܥܡ ܠܘܚܐ (table) ܠܦܘܬ APA ܘܡܐܡܪܐ ܕܬܘܢܝܐ (report sentence) ܒܣܘܪܝܬ ܘܒܐܢܓܠܝܙܝܐ:
ܡܛܝܒܘܬܐ ܕܝܗܝ̈ܒܬܐ
ܡܢ SPSS ܠܐܩܣܠ – ܦܐܝܠ .sav ܟܥܐܠ، ܬܠܬܐ ܡܦܩ̈ܬܐ ܕ-SPSS ܟܦܠܛܝ. ܛܘܦܣܐ ܬܩܝܢܐ – ܣܕܪܐ = ܡܫܬܘܬܦܢܐ، ܥܡܘܕܐ = ܡܫܬܚܠܦܢܐ – ܝܠܗ ܡܦܩܢܐ ܕܡܩܘܒܠܐ ܝܠܗ ܡܢ ܟܠ ܡܐܢܐ ܕܟܢܫܐ ܓܘ ܠܘܚܐ 7؛ ܒܘܚܪܢܐ ܕܢܘܪܡܠܝܘܬܐ ܩܕܡ ܒܘܚܪ̈ܢܐ.
ܐܣܘܪܐ ܣܛܐܛܝܣܛܝܩܝܐ (statistical association)
ܐܣܘܪ̈ܐ ܕܚܕ̈ܕܐ – Pearson ܘ-Spearman · ܨܘܪܬܐ ܕܒܕܪܐ · ܪܝܓܪܫܢ ܣܪܛܢܝܐ · ܪܝܓܪܫܢ ܠܘܓܝܣܛܝܩܝܐ · ܡܪܟܟܢܘܬܐ ܘܡܨܥܝܘܬܐ · ܦܘܫܩܐ ܕܫܒ̈ܝܠܐ · ܦܘܫܩܐ ܕܥܠ̈ܠܬܐ ܡܒܨܝܢܐ · ܦܘܫܩܐ ܕܥܠ̈ܠܬܐ ܡܫܪܪܢܐ · ܡܘܕܝܠ ܕܫܘܝ̈ܘܬܐ ܒܢܝܢܝ̈ܬܐ (SEM) · ܦܘܫܩܐ ܕܥܢܩܘ̈ܕܐ · ܦܘܫܩܐ ROC.
ܪܫܝܡܬܐ ܓܡܝܪܬܐ ܕܡܚܫܒ̈ܢܐ ܐܝܬܠܗ̇ ܓܘ tabs ܕܒܪܫܐ ܕܦܐܬܐ. ܦܐ̈ܬܐ ܐܚܪ̈ܢܝܬܐ ܕܡܕܒܪܢܐ (guide) ܕܡܢܬܐ ܐ: NLP ܒܠܫܢܐ ܥܒܪܝܐ · ܝܘܠܦܢܐ ܕܡܟܝܢܐ ܩܐ ܒܨܘܝܐ ܟܢܫܝܐ · ܡܚܘ̈ܝܢܐ ܕܥܒܕܐ ܘܫܘܪܪܐ · ܝܘܠܦܢܐ ܕܠܐ ܡܕܒܪܢܐ.
ܡܒܘ̈ܥܐ
Carter, B. W. (2013). Digital humanities: Current perspective, practices, and research (Cutting-Edge Technologies in Higher Education, Vol. 7). Emerald.
Cioffi-Revilla, C. (2017). Introduction to computational social science: Principles and applications (2nd ed.). Springer. https://doi.org/10.1007/978-3-319-50131-4
Dawson, C. (2020). A–Z of digital research methods. Routledge.
Drucker, J. (2021). The digital humanities coursebook: An introduction to digital methods for research and scholarship. Routledge.
Drucker, J., & Albrezzi, F. (2026). The digital humanities coursebook: Applied concepts and critical approaches (2nd ed.). Routledge. https://doi.org/10.4324/9781003589792
Edelmann, A., Wolff, T., Montagne, D., & Bail, C. A. (2020). Computational social science and sociology. Annual Review of Sociology, 46, 61-81. https://doi.org/10.1146/annurev-soc-121919-054621
Grimmer, J., Roberts, M. E., & Stewart, B. M. (2022). Text as data: A new framework for machine learning and the social sciences. Princeton University Press.
Jockers, M. L. (2013). Macroanalysis: Digital methods and literary history. University of Illinois Press.
Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A.-L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., & Van Alstyne, M. (2009). Computational social science. Science, 323(5915), 721-723. https://doi.org/10.1126/science.1167742
Lazer, D. M. J., Pentland, A., Watts, D. J., Aral, S., Athey, S., Contractor, N., Freelon, D., Gonzalez-Bailon, S., King, G., Margetts, H., Nelson, A., Salganik, M. J., Strohmaier, M., Vespignani, A., & Wagner, C. (2020). Computational social science: Obstacles and opportunities. Science, 369(6507), 1060-1062. https://doi.org/10.1126/science.aaz8170
Moretti, F. (2013). Distant reading. Verso.
Rieder, B. (2015). YouTube Data Tools (Version 1.x) [Computer software]. https://ytdt.digitalmethods.net
Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1-36. https://doi.org/10.18637/jss.v048.i02
Salganik, M. J. (2018). Bit by bit: Social research in the digital age. Princeton University Press. https://www.bitbybitbook.com
Schreibman, S., Siemens, R., & Unsworth, J. (Eds.). (2016). A new companion to digital humanities. Wiley Blackwell. https://doi.org/10.1002/9781118680605
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., . . . Mons, B. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, Article 160018. https://doi.org/10.1038/sdata.2016.18