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2025年9月30日のJAIST研究科セミナーの講演資料です

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1. ޡ৘ใɾӄ๳࿦ͱࣾձͷ෇͖߹͍ํ  ೝ஌ɾ৴๬ɾߦಈͷஈ֊తϑϨʔϜϫʔΫ͔Β  ଜࢁଠҰ ԣ඿ࠃཱେֶ .BJM
   NVSBZBNBUBJDIJCT!ZOVBDKQ 20250930 JAIST研究科セミナー
2. 2 ଜࢁ ଠҰ l ॴଐ
   ԣ඿ࠃཱେֶ ؀ڥ৘ใݚڀӃ ॿڭ l ژ౎େֶ๏ֶ෦ଔ l ಸྑઌ୺Պֶٕज़େֶӃେֶ ৘ใՊֶྖҬ म࢜ത࢜ଔ l ओͳݚڀ ڵຯ
   τϐοΫ l 8FCσʔλϚΠχϯά l ܭࢉࣾձՊֶ l ࣌ܥྻϞσϧ l ࣗવݴޠॲཧ ࣗݾ঺հ
3. 3 ࣗݾ঺հ 対象：⼈々の⾏動が反映されたWebデータ ・⼈々の⽂化や⾏動を理解 (計算社会科学) ・理解するための技術開発 (データマイニング、⾃然⾔語処理, etc.) 私達の社会 (Physics world) ⼤規模なWebデータ 投稿や検索 研究対象 社会を反映
4. 4 Xihao Piao, Zheng Chen, Taichi Murayama, Yasuko Matsubara, and Yasushi Sakurai. "Fredformer: Frequency Debiased Transformer for Time Series Forecasting.", In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '24). 2400–2410, 2024. Taichi Murayama, Yasuko Matsubara, and Yasushi Sakurai. "Mining Reaction and Diffusion Dynamics in Social Activities." Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM’22). 2022. ࣌ܥྻ༧ଌɾ࣌ܥྻϞσϧ
5. 5 Taichi Murayama, Shoko Wakamiya, Eiji Aramaki, “Mitigation of Diachronic Bias in Fake News Detection Dataset”, In Proceedings of the 7th Workshop on Noisy User-generated Text (W-NUT’21), EMNLP Workshop, 2021 時間の流れに頑健なフェイク ニュース検出モデル構築 ࣗવݴޠॲཧ ⼤規模⾔語モデルは物語性の有無 で記憶保存能⼒に違いがあるか？
7. 7 ൃද಺༰  ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε  ӄ๳࿦ͷӨڹͱͦͷରࡦ  ӄ๳࿦ରࡦͷର৅Λ୳͢ݚڀ
8. 8 ൃද಺༰  ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε  ӄ๳࿦ͷӨڹͱͦͷରࡦ  ӄ๳࿦ରࡦͷର৅Λ୳͢ݚڀ
9. 9 ϑΣΠΫχϡʔεͷ൙ཞ બڍલϲ݄Ͱ໿ສճɺީิऀਓ τϥϯϓࢯ
   ΫϦϯτϯࢯ ͷϑΣΠΫχϡʔε͕'BDFCPPLͰ֦ࢄ Allcott, Hunt, and Matthew Gentzkow. "Social media and fake news in the 2016 election." Journal of economic perspectives 31.2 (2017): 211-36. ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε
10. 10 ϑΣΠΫχϡʔεͷ൙ཞ 5G network spreads COVID-19 Vitamin C cures COVID-19 ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε
11. 11 ϑΣΠΫχϡʔε࡞੒ͷϝϦοτ https://www.newsweek.com/2017/06/16/big-data-mines-personal-info-manipulate-voters-623131.html ੈ࿦ૢ࡞ ͓ۚṶ͚ https://www.nbcnews.com/news/world/fake-news-how-partying-macedonian-teen- earns-thousands-publishing-lies-n692451 ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε
12. 12 ϑΣΠΫχϡʔεͷඃ֐ ๫ಈࣄ݅ ͓ۚṶ͚ https://www.npr.org/2018/07/18/629731693/fake-news-turns-deadly-in-india https://www.washingtonpost.com/news/worldviews/wp/2013/04/23/syrian-hackers-claim-ap-hack-that- tipped-stock-market-by-136-billion-is-it-terrorism/ גՁٸམ ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε
13. 13 ϑΣΠΫχϡʔεͷඃ֐ɿ੓࣏ ⼭⼝真⼀（2022）『ソーシャルメディア解体全書』、勁草書房 l ϑΣΠΫχϡʔεʹΑͬͯର৅ ΁ͷࢧ࣋Λ௿Լͤ͞ΔޮՌ l ಛʹऑ͍ࢧ࣋Λ͍͑ͯͨਓʑʹ ର͠ϑΣΠΫχϡʔε͸ޮՌత ʹӨڹΛ༩͑Δ ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε
14. 14 ιʔγϟϧϝσΟΞ͸৘ใ֦ࢄ૷ஔ ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε
15. 15 l ೔ຊͰ͸ϛυϧϝσΟΞͷଘࡏ͕ιʔγϟϧϝσΟΞͰͷ ϑΣΠΫχϡʔε֦ࢄͷҰ໾Λ୲͍ͬͯΔͱ͍͏ࢦఠ https://www.soumu.go.jp/main_content/000749423.pdf ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε
16. 16 ϑΣΠΫχϡʔεͷ֦ࢄ͸଎ͨ͘͘͞Μ఻ΘΔ ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε Vosoughi, Soroush, Deb Roy, and Sinan Aral. "The spread of true and false news online." science 359.6380 (2018): 1146-1151. https://www.soumu.go.jp/main_content/000630427.pdf l ಛʹ੓࣏ɺϏδωεɺઓ ૪ɺՊֶͳͲͷ࿩୊Ͱ֦ ࢄ͞Ε΍͍͢܏޲ l #PUͷޮՌ͸ҙ֎ͱখ͍͞ 届く速さ
17. 17 ϑΣΠΫχϡʔεΛ֦ࢄ͢ΔϢʔβͱ͸ʁ ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε Yamaguchi, Shinichi, and Tsukasa Tanihara. "Relationship between misinformation spreading behaviour and true/false judgments and literacy: an empirical analysis of COVID-19 vaccine and political misinformation in Japan." Global Knowledge, Memory and Communication (2023). ౰વ͕ͩɺͦͷχϡʔεΛʮਖ਼͠ ͍ʯͱ৴ͨ͡ΓϝσΟΞɾϦςϥ γʔ͕௿͍ਓ͕֦ࢄ͠қ͍ ϑΣΠΫχϡʔεͷڞ༗ͷ͸ͷ ϢʔβʹΑΔ΋ͷͰɺߴྸऀ΍ӈدΓͷ ੓࣏ࢥ૝ͷϢʔβ͕ڞ༗͠΍͍͢ Grinberg, Nir, et al. "Fake news on Twitter during the 2016 US presidential election." Science 363.6425 (2019): 374-378.
18. 18 ϑΣΠΫχϡʔε͸ͲͷΑ͏ʹ֦ࢄ͞ΕΔ͔ʁ l ϑΣΠΫχϡʔεͷ4/4্ͷ౤ߘ࣌ܥྻ͔Βɺ֦ࢄΛϞσϦϯά l ϑΣΠΫχϡʔεͱ௨ৗͷχϡʔεͰ֦ࢄͷܗଶ͸ҟͳΔ͔ʁ ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε Timeline 2020/01/01 12:00 この猫でかすぎ！ Modeling 投稿確率 Taichi Murayama, Shoko Wakamiya, Eiji Aramaki, Ryota Kobayashi “Modeling the spread of fake news on Twitter”, PLOS ONE 16(4): e0250419, 2021.
19. 19 ϑΣΠΫχϡʔε͸ͲͷΑ͏ʹ֦ࢄ͞ΕΔ͔ʁ ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε このニュースめちゃ くちゃ⾯⽩いー 拡散しよ！ え、このニュース はフェイクなの！ 拡散しよ！ 1回⽬拡散 2回⽬拡散 Taichi Murayama, Shoko Wakamiya, Eiji Aramaki, Ryota Kobayashi “Modeling the spread of fake news on Twitter”, PLOS ONE 16(4): e0250419, 2021. 通常のニュース フェイクニュース
20. 20 ϑΣΠΫχϡʔε͸ͲͷΑ͏ʹ֦ࢄ͞ΕΔ͔ʁ ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε Taichi Murayama, Shoko Wakamiya, Eiji Aramaki, Ryota Kobayashi “Modeling the spread of fake news on Twitter”, PLOS ONE 16(4): e0250419, 2021. 最初の拡散 2回⽬の拡散 𝜆 𝑡 = 𝑝! 𝑡 ℎ! 𝑡 + 𝑝" (𝑡)ℎ" (𝑡) 訂正時間𝑡! でカスケードを分割 ℎ∗ 𝑡 = ) $:&! 𝑑$ 𝜙(𝑡 − 𝑡$ ) 感染率 どれだけの⼈が 覚えているか 感染率 どれだけの⼈が 覚えているか 𝑝(𝑡): 時間tにおける感染率， 𝑑! : i番⽬のイベントでの観測者(フォロワー数) 𝑡! : i番⽬のイベントの投稿時間 𝜙: どの程度記憶しているかを表した関数
21. 21 ϑΣΠΫχϡʔε͸ͲͷΑ͏ʹ֦ࢄ͞ΕΔ͔ʁ ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε ྫỚʮτϧί͕ԯԁ೔ຊʹد෇ʯͱ͍͏ϑΣΠΫχϡʔε l గਖ਼࣌ؒ𝑡! = 37લޙͷ౤ߘςΩετΛ8PSEͰൺֱ l 𝑡! ҎલͰ͸ʮ਌೔ࠃʯͱ͍ͬͨͦͷχϡʔεʹؔ͢Δޠ l 𝑡! ҎޙͰ͸ʮ୆࿷ʯʹؔ͢ΔχϡʔεͱҰׅͰσϚͱࢦఠ Taichi Murayama, Shoko Wakamiya, Eiji Aramaki, Ryota Kobayashi “Modeling the spread of fake news on Twitter”, PLOS ONE 16(4): e0250419, 2021.
22. 22 ϑΣΠΫχϡʔεΛݕग़͢ΔࢼΈ ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε l ͲͷΑ͏ͳಛ௃Λ༻͍Δͷ͔ʁ l ༻͍ͨಛ௃Λ্ख͘׆༻Ͱ͖Δ͔ػցֶशϞσϧΛͲͷΑ͏ʹ ߏங͢Δͷ͔ʁ l ͲͷΑ͏ͳ෇ՃՁ஋ΛՃ͑Δͷ͔ʁʢ৴པੑͳͲʣ 機械学習モデル フェイクニュースの 可能性のある投稿に 関する情報 (特徴量) ⼊⼒ 出⼒ Fake or True
23. 23 ϑΣΠΫχϡʔεΛݕग़Ϟσϧͷྫ ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε ςΩετ৘ใ΍ڞ༗ͨ͠ Ϣʔβͷಛ௃ɺ֦ࢄͷ࣌ ܥྻΛ༻͍ͯɺϑΣΠΫ χϡʔε͔Ͳ͏͔Λ൑ఆ ൑ఆʹ஫໨ͨ͠ՕॴΛ ՄࢹԽʢઆ໌ੑͷ෇༩ʣ Taichi Murayama, Shoko Wakamiya, Eiji Aramaki “Fake News Detection using Temporal Features Extracted via Point Process ” In Proceedings of CySoc 2020 International Workshop on Cyber Social Threats, ICWSM Workshop, 2020.
24. 24 ϑΣΠΫχϡʔεΛݕग़Ϟσϧͷ՝୊ ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε l ೥ͷσʔλͰߏஙͨ͠ϑΣΠΫχϡʔεݕग़Ϟσϧ͕೥ ͷσʔλʹରԠͰ͖Δͷ͔ʁ EJBDISPOJD
    CJBTͷଘࡏ l ϞσϧΛຖ೥ߋ৽͠ଓ͚Δͱ͍͏ͷ͸େม l --. 3"(ͷ׆༻ l ߏங͞ΕΔػցֶशϞσϧͷ൑அ͸ਖ਼͍͠Θ͚Ͱ͸ͳ͍ l ਖ਼͍͠৘ใΛϑΣΠΫͱࢦఠ͢Δةݥੑʹ͍ͭͯ ِཅੑ΍ِӄੑ l ػցֶशϞσϧͷϒϥοΫϘοΫε໰୊ l ൑அͷࠜڌ΍࢓૊Έ͕Θ͔Βͳ͍ͱਓؒ͸ͦͷϞσϧΛ৴͖͡Εͳ͍ l େྔʹଘࡏ͢Δ౤ߘΛͲͷΑ͏ʹࡹ͔͘
25. 25 "WBJMBCJMJUZ
    )FVSJTUJD ʢར༻ՄೳੑώϡʔϦεςΟοΫʣ ͳͥਓʑ͸ϑΣΠΫχϡʔεΛ৴ͯ͡͠·͏ͷ͔ʁ l ࠷ۙ໨ʹͨ͠৘ใ΍සൟʹ઀৮͢Δ৘ใ ͕൑அʹӨڹΛ༩͑Δ͜ͱ l ϝσΟΞ΍4/4Ͱසൟʹ໨ʹ͢ΔϑΣΠ Ϋχϡʔε͸ɺޡͬͨ৘ใ͕ࣄ࣮ͱͯ͠ ೝࣝ͞Ε΍͍͢ Pennycook, Gordon, et al. "Shifting attention to accuracy can reduce misinformation online." Nature 592.7855 (2021): 590-595.
26. 26 όοΫϑΝΠΞʔޮՌ ͳͥਓʑ͸ϑΣΠΫχϡʔεΛ৴ͯ͡͠·͏ͷ͔ʁ l ݸਓͷ৴೦ʹ߹Θͳ͍గਖ਼Λ༩͑ΒΕͨ ͱͯ͠΋ɺͦͷగਖ਼Λ৴ͣ͡ɺ͔͑ͬͯ గਖ਼ʹΑͬͯݸਓͷ৴೦ΛڧΊΔޮՌ l όοΫϑΝΠΞޮՌΛࣔ͢Ϣʔβ͸ɺෆ ฏෆຬ΍εϥϯάతͳදݱΛ༻͍Δ͜ͱ ͕ଟ͍ Nyhan, Brendan, and Jason Reifler. "When corrections fail: The persistence of political misperceptions." Political Behavior 32.2 (2010): 303-330. Jiang, Shan, and Christo Wilson. "Linguistic signals under misinformation and fact-checking: Evidence from user comments on social media." Proceedings of the ACM on Human-Computer Interaction 2.CSCW (2018): 1-23.
27. 27 հೖͷՄೳੑ ͳͥਓʑ͸ϑΣΠΫχϡʔεΛ৴ͯ͡͠·͏ͷ͔ʁ l φοδ
    ֦ࢄͷલʹ࠶ߟΛଅ͢ઃܭ΍ɺ ʮଟ͘ͷਓ͸͜ͷ৘ใΛڞ༗͠ͳ͍ʯͱ͍ ͏ࣾձنൣͷఏࣔ l ڭҭ
    ͋Β͔͡Ίయܕతͳޡ৘ใͷखޱΛ ఏࣔ͠ɺ໔ӸΛ͚ͭΔɻϝσΟΞɾϦςϥ γʔڭҭͳͲɻ l ൓࿦ઓུ
    ൓࿦΍ϑΝΫτνΣοΫʹΑΔ గਖ਼ Kozyreva, Anastasia, et al. "Toolbox of individual-level interventions against online misinformation." Nature Human Behaviour 8.6 (2024): 1044-1052.
28. 28 φοδΛ׆༻ͨ͠ϑΣΠΫχϡʔε΁ͷରࡦ ͳͥਓʑ͸ϑΣΠΫχϡʔεΛ৴ͯ͡͠·͏ͷ͔ʁ l Ϣʔβʔʹର͠ɺʮݟग़͠ͷਖ਼֬ੑΛධՁͯͩ͘͠͞ ͍ʯͱ؆୯ͳ࣭໰ΛڬΉ͜ͱͰɺͦͷޙͷϑΣΠΫ χϡʔεͷڞ༗͕ݮগ 1FOOZDPPL
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    3FWJFX Fazio, Lisa. "Pausing to consider why a headline is true or false can help reduce the sharing of false news." Harvard Kennedy School Misinformation Review 1.2 (2020). Pennycook, Gordon, et al. "Shifting attention to accuracy can reduce misinformation online." Nature 592.7855 (2021): 590-595.
29. 29 ΫΠζΛ׆༻ͨ͠ϑΣΠΫχϡʔε΁ͷରࡦ ͳͥਓʑ͸ϑΣΠΫχϡʔεΛ৴ͯ͡͠·͏ͷ͔ʁ l ϑΣΠΫχϡʔεΛݟ͔ͯΒగਖ਼͢ΔͷͰ ͸ͳ͘ɺʮڭҭʯͱͯ͠ϑΣΠΫχϡʔε ʹର͢ΔϫΫνϯΛ઀छ l ΫΠζܗࣜͰֶͿ͜ͱͰɺϑΣΠΫχϡʔ εʹରͯ͠ὃ͞Εʹ͘͘ͳΔޮՌΛൃش Roozenbeek, Jon, and Sander van der Linden. "Breaking Harmony Square: A game that “inoculates” against political misinformation." The Harvard Kennedy School Misinformation Review (2020).
30. 30 ൃද಺༰  ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε  ӄ๳࿦ͷӨڹͱͦͷରࡦ  ӄ๳࿦ରࡦͷର৅Λ୳͢ݚڀ
31. 31 l 8JLJQFEJBͷܝࡌ͚ͩͰ΋ݸҎ্ͷӄ๳࿦ l ϢμϠӄ๳࿦ɺέϜτϨΠϧɺδϣϯɾ'ɾέωσΟ҉ࡴɺΠϧϛφςΟɺ ςϩࣄ݅ɺ΢Πϧεӄ๳࿦ FUDʜ ӄ๳࿦ͷӨڹͱͦͷରࡦ
32. 32 l ͦ΋ͦ΋ӄ๳࿦ $POTQJSBDZ
    5IFPSJFT ͱ͸ l ੓࣏తɾࣾձతͳग़དྷࣄ΍ɺࣄ݅΍ࣄނͳͲͷԿΒ͔ͷग़དྷࣄʹ͍ͭͯɺ ͦͷഎޙʹڧେ͔ͭڧྗͳूஂɾ૊৫ʹΑΔྗ͕ಇ͍͍ͯΔͱཧղ͠ɺઆ ໌͠Α͏ͱ͢Δߟ͑ํ l "UUFNQU
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    <> l ʮϑΣΠΫχϡʔεʯͱͷҧ͍ l ϑΣΠΫχϡʔεɿҙਤతʹڏِͷ৘ใΛ޿ΊΔ͜ͱʹΑͬͯɺޡͬͨࣄ ࣮Λ৴ͤ͡͞Δχϡʔεهࣄ΍ίϯςϯπ<> l ӄ๳࿦͸ඞͣ͠΋ʮޡΓʯͱ͸ݶΒͳ͍ʢະ֬ఆࣄ߲Ͱ͋Δ͜ͱ΋ଟ͍ʣ ӄ๳࿦ͷӨڹͱͦͷରࡦ [1] Douglas, Karen M., et al. "Understanding conspiracy theories." Political psychology 40 (2019): 3-350. [2] Gelfert, Axel. "Fake news: A definition." Informal logic 38.1 (2018): 84-117.
33. 33 ӄ๳࿦ͷӨڹͱͦͷରࡦ ӄ๳࿦Ϡό͍Β͍͚͠ Ͳɺ৴ͯ͡ΔਓͳΜͯ ΄΅ډͳ͍Ͱ͠ΐɻ
34. 34 ӄ๳࿦ͷӨڹͱͦͷରࡦ ӄ๳࿦Ϡό͍Β͍͚͠ Ͳɺ৴ͯ͡ΔਓͳΜͯ ΄΅ډͳ͍Ͱ͠ΐɻ ҙ֎ͱ৴ͯ͡Δਓ͸ଟ͍ʜʂ ྫ
    ʮͷഎޙʹ͍Δͷ͸ʁʯͱ͍͏໰͍ ͰΞϧΧΠμҎ֎ͱ౴͑ͨࠃ͕ա൒਺Ҏ্ <> [3] Allen, J. "No consensus on who was behind Sept 11: Global Poll. Reuters." (2008).
35. 35 ྫ
    ೔ຊͰͷӄ๳࿦ l ೔ຊࡏॅͷ ਓʹରͯ͠ӄ๳࿦ʹ͍ͭͯ৴ͯ͡Δ͔Λௐࠪ ӄ๳࿦ͷӨڹͱͦͷରࡦ 0% 20% 40% 60% 80% 100% 地 球 温 暖 化 ワ クチ ン 副 作 ⽤ 裏 の 団 体 在 ⽇ 外 国 ⼈ ⼈ ⼯ 地 震 ヒト 型 爬 ⾍ 類 コロ ナ は 存 在 し な い 宇 宙 ⼈ との 接 触 9.11テ ロ ⽶ 国 選 挙 不 正 ケ ム ト レ イ ル 知っている 正しいと思う ର৅ͷӄ๳࿦Λ஌ͬͯΔ ର৅ͷӄ๳࿦Λਖ਼͍͠ͱࢥ͏
36. 36 ӄ๳࿦Λ৴ͨ͜͡ͱʹΑΔਓؒؔ܎ͷѱԽ ӄ๳࿦ͷӨڹͱͦͷରࡦ [4] ⼭⼝真⼀他, Innovation Nippon 2024「偽・誤情報、ファクト チェック、教育啓発に関する調査」 ӄ๳࿦Λਖ਼͍͠ͱࢥͬͨ͜ͱ ʹΑΓਓؒؔ܎ѱԽΛܦݧ͠ ͨਓ͕
    r ఔ౓ଘࡏ <>
37. 37 ӄ๳࿦΍ޡͬͨ৘ใͷՄೳੑ͸ਓͷ൑அΛ஗ΒͤΔ l ʮޡ৘ใ͕͋Δ͔΋͠Εͳ͍ʯͱࢥ͍ͳ͕Βχϡʔεͷݟग़͠Λݟ Δͱɺ໿ඵ΋ؾʹͳΔݟग़͠ΛબͿͷʹ͔͔Δ͕࣌ؒ૿Ճ <> ӄ๳࿦ͷӨڹͱͦͷରࡦ
38. 38 ӄ๳࿦ʹΑΔଞͷѱӨڹ l ӄ๳࿦΁ͷ๫࿐͕ɺݽಠײͷ૿େʹ ܨ͕Γɺকདྷతʹ೔ৗ൜ࡑʹؔ༩͞ ͤΔՄೳੑΛ૿େ <> l ൓ϫΫνϯͷҙݟͷٸ૿͕͜ͷ·· ଓ͘ͱɺ೥ޙʹ͸͜ΕΒͷҙݟ͕ ओྲྀͱͳΔՄೳੑΛࣔࠦ <> ӄ๳࿦ͷӨڹͱͦͷରࡦ [5] Jolley, Daniel, et al. "Belief in conspiracy theories and intentions to engage in everyday crime." British Journal of Social Psychology 58.3 (2019): 534-549. [6] Johnson, Neil F., et al. "The online competition between pro-and anti- vaccination views." Nature 582.7811 (2020): 230-233.
39. 39 ӄ๳࿦Λ৴͡Δਓͷଐੑʹ͍ͭͯ ӄ๳࿦ͷӨڹͱͦͷରࡦ [7] Hornsey, Matthew J., et al. "Individual, intergroup and nation-level influences on belief in conspiracy theories." Nature Reviews Psychology 2.2 (2023): 85-97. [8] Douglas, Karen M., and Robbie M. Sutton. "What are conspiracy theories? A definitional approach to their correlates, consequences, and communication." Annual review of psychology 74.1 (2023): 271-298. [9] Mahl, Daniela, Mike S. Schäfer, and Jing Zeng. "Conspiracy theories in online environments: An interdisciplinary literature review and agenda for future research." New media & society 25.7 (2023): 1781-1801.
40. 40 ਓʑͷ࣋ͭೝ஌όΠΞε ӄ๳࿦ͷӨڹͱͦͷରࡦ l ଟ͘ͷਓʑ͸ܦݧ΍௚ײ͔Β ޡͬͨ൑அΛͯ͠͠·͏ l ֬ূόΠΞε l ൺྫόΠΞε l ͜ΕΒͷόΠΞε͕ਓʑʹӄ ๳࿦Λ৴ͤ͡͞ΔޮՌΛ΋ͨ Β͢ҰํͰɺӄ๳࿦ରࡦʹ࢖ ͑ΔՄೳੑ΋ൿΊ͍ͯΔ https://en.wikipedia.org/wiki/Cognitive_bias
41. 41 ӄ๳࿦Λ৴͡Δਓͷଐੑͷྫ l ௚ײతࢥߟͷߴ͞ɺ෼ੳతࢥߟͷ௿͞ <> l ύϥϊΠΞɺࣗݾѪͷڧ͞ <> l ஥ؒ͸ͣΕͷײ֮ <>
    ࢠͲ΋࣌୅ͷݽಠײ <> l फڭత 
    εϐϦνϡΞϧ΁ͷ܏౗ <>
    l কདྷͷࠃՈͷܦࡁྗʹର͢Δෆ҆
    ੓෎΁ͷ৴པͷ௿͞ <> ӄ๳࿦ͷӨڹͱͦͷରࡦ [10] Swami, Viren, et al. "Analytic thinking reduces belief in conspiracy theories." Cognition 133.3 (2014): 572-585. [11] Imhoff, Roland, and Pia Lamberty. "How paranoid are conspiracy believers? Toward a more fine‐grained understanding of the connect and disconnect between paranoia and belief in conspiracy theories." European journal of social psychology 48.7 (2018): 909-926. [12] Stasielowicz, Lukasz. "Who believes in conspiracy theories? A meta-analysis on personality correlates." Journal of Research in Personality 98 (2022): 104229. [13] Poon, Kai-Tak, Zhansheng Chen, and Wing-Yan Wong. "Beliefs in conspiracy theories following ostracism." Personality and Social Psychology Bulletin 46.8 (2020): 1234-1246. [14] Bierwiaczonek, Kinga, et al. "Loneliness trajectories over three decades are associated with conspiracist worldviews in midlife." Nature Communications 15.1 (2024): 3629. [15] Hornsey, Matthew J., et al. "Multinational data show that conspiracy beliefs are associated with the perception (and reality) of poor national economic performance." European Journal of Social Psychology 53.1 (2023): 78-89.
42. 42 ཈੍ํ๏ɿ4PDJBM
    .FEJB
    #BO ӄ๳࿦ͷӨڹͱͦͷରࡦ
43. 43 4PDJBM
    .FEJB
    #BO͞ΕͨϢʔβ΍ίϛϡχςΟ͸ɺผͷ4PDJBM
    .FEJBҠಈͯ͠׆ಈΛଓ͚Δ <> l 2"OPO͸3FEEJU
    ˠ
    1PBM
    
    7PBUͳͲͷ4/4ʹҠಈ l ίϛϡχςΟด࠯࣌ظΛ࣮ࣔͯ͠ࡍʹด࠯͢Δ·Ͱͷؒͷ࣌ؒͰɺҎ߱৔ ॴΛܾఆ l ׆ಈ͢ΔϢʔβ਺ࣗମ͸ॖখ͢Δ΋ͷͷɺҰਓ͋ͨΓͷ׆ಈྔ͸େ͖͘ม ΘΒͣ ӄ๳࿦ͷӨڹͱͦͷରࡦ [16] Monti, Corrado, et al. "Online conspiracy communities are more resilient to deplatforming." PNAS nexus 2.10 (2023): pgad324.
44. 44 4PDJBM
    .FEJB
    #BO͞ΕͨϢʔβ΍ίϛϡχςΟ͸ɺผͷ4PDJBM
    .FEJBҠಈͯ͠׆ಈΛଓ͚Δ <> l ಟੑͷ͋Δίϝϯτ͸Ҡߦޙʹ૿Ճ܏޲ʂ 
      ӄ๳࿦ͷӨڹͱͦͷରࡦ [16] Monti, Corrado, et al. "Online conspiracy communities are more resilient to deplatforming." PNAS nexus 2.10 (2023): pgad324.
45. 45 ݸਓʹର͢Δ཈੍ํ๏ɿ൓࿦ l ͨͩʮӄ๳࿦ʯͱࢦఠ͢Δ͚ͩͰ͸ɺٯޮՌʢCBDLGJSFޮՌʣ<> ӄ๳࿦ͷӨڹͱͦͷରࡦ [17] O’Mahony, Cian, et al. "The efficacy of interventions in reducing belief in conspiracy theories: A systematic review." Plos one 18.4 (2023): e0280902. [18] Stojanov, Ana. "Reducing conspiracy theory beliefs." Psihologija 48.3 (2015): 251-266. [19] Orosz, Gábor, et al. "Changing conspiracy beliefs through rationality and ridiculing." Frontiers in Psychology 7 (2016): 1525.
46. 46 όοΫϑΝΠΞʔޮՌ ӄ๳࿦ͷӨڹͱͦͷରࡦ l ݸਓͷ৴೦ʹ߹Θͳ͍గਖ਼Λ༩͑ΒΕͨ ͱͯ͠΋ɺͦͷగਖ਼Λ৴ͣ͡ɺ͔͑ͬͯ గਖ਼ʹΑͬͯݸਓͷ৴೦ΛڧΊΔޮՌ l όοΫϑΝΠΞޮՌΛࣔ͢Ϣʔβ͸ɺෆ ฏෆຬ΍εϥϯάతͳදݱΛ༻͍Δ͜ͱ ͕ଟ͍ Nyhan, Brendan, and Jason Reifler. "When corrections fail: The persistence of political misperceptions." Political Behavior 32.2 (2010): 303-330. Jiang, Shan, and Christo Wilson. "Linguistic signals under misinformation and fact-checking: Evidence from user comments on social media." Proceedings of the ACM on Human-Computer Interaction 2.CSCW (2018): 1-23.
47. 47 ݸਓʹର͢Δ཈੍ํ๏ɿ൓࿦ l ͨͩʮӄ๳࿦ʯͱࢦఠ͢Δ͚ͩͰ͸ɺٯޮՌʢCBDLGJSFޮՌʣ<> l ࠜڌ΍ূڌΛ࣋ͬͯ൓࿦͢ΔߦҝʢDPVOUFSBSHVNFOUTʣ΋ӄ๳ ࿦త৴೦Λม͑ͤ͞ΔޮՌ͸͔ͳΓখ͍͞ <> l ૬खͷڞײײ֮ʹૌ͔͚͑ͯ൓࿦͢ΔߦҝʢFNQBUIZCBTFE JOUFSWFOUJPOʣ΍૬खΛ͚͋ͯ͟൓࿦͢ΔߦҝʢSJEJDVMFʣ͸Ͳͪ Β΋΄ͱΜͲޮՌ͕ແ͍ <> ӄ๳࿦ͷӨڹͱͦͷରࡦ [17] O’Mahony, Cian, et al. "The efficacy of interventions in reducing belief in conspiracy theories: A systematic review." Plos one 18.4 (2023): e0280902. [18] Stojanov, Ana. "Reducing conspiracy theory beliefs." Psihologija 48.3 (2015): 251-266. [19] Orosz, Gábor, et al. "Changing conspiracy beliefs through rationality and ridiculing." Frontiers in Psychology 7 (2016): 1525.
48. 48 ݸਓʹର͢Δ཈੍ํ๏ɿੜ੒"*Λ༻͍ͨ൓࿦ ӄ๳࿦ͷӨڹͱͦͷରࡦ [20] Costello, Thomas H., Gordon Pennycook, and David G. Rand. "Durably reducing conspiracy beliefs through dialogues with AI." Science 385.6714 (2024): eadq1814. l ੜ੒"*Ϟσϧ (15 ʹ൓࿦ͯ͠΋ Β͏ͱޮՌ͋Γ<> l ӄ๳࿦৴೦͸ฏۉˋݮগɻ ϲ݄ޙͷ௥੻ௐࠪͰ΋ޮՌ͕ଓ͍ ͍ͯΔ͜ͱΛ֬ೝ l ੜ੒"*Ϟσϧͷఏࣔ͢Δ&WJEFODFͰ ڏِͷ΋ͷ͸΄ͱΜͲແ͠ ໿
49. 49 ݸਓʹର͢Δ཈੍ํ๏ɿࢥߟೳྗͷ޲্ l ෼ੳతࢥߟ΍ೝ஌తख़ྀೳྗ͸ޡ৘ใ΍ӄ๳࿦ͷ৴೦ͷෛͷ૬ؔ <> l ʮΏͬ͘Γߟ͑Δʯ͜ͱΛࢦࣔ͢Δ͚ͩͰӄ๳࿦ͷ৴೦ΛऑΊΔ ܏޲ <> l ϑϥϯεͷதֶੜʹ$SJUJDBM 5IJOLJOHͷतۀΛ͢Δ͜ͱͰɺӄ๳ ࿦త৴೦ΛऑΊΔޮՌ <> ӄ๳࿦ͷӨڹͱͦͷରࡦ [21] Swami, Viren, et al. "Analytic thinking reduces belief in conspiracy theories." Cognition 133.3 (2014): 572-585. [22] Bago, Bence, David G. Rand, and Gordon Pennycook. "Fake news, fast and slow: Deliberation reduces belief in false (but not true) news headlines." Journal of experimental psychology: general 149.8 (2020): 1608. [23] Caroti, Denis, et al. "Critical Thinking Education to Decrease Conspiracy and Paranormal Beliefs Among Secondary School Students: a Phase I Trial." (2023).
50. 50 ݸਓʹର͢Δ཈੍ํ๏ɿ༧๷઀छ 
    ڭҭ ӄ๳࿦ͷӨڹͱͦͷରࡦ l ࠷΋ӄ๳࿦৴೦Λ௿Լͤ͞ΔՄೳੑ͕ߴ͍ͭͷ཈੍ํ๏ l ༧๷઀छʢJOGPSNBUJPO
    JOPDVMBUJPOʣɿӄ๳࿦઀৮લʹ๷ޚతͳೝ஌ε λϯεΛܗ੒͢ΔͨΊʹɺલ΋ͬͯӄ๳࿦ͷ࿦ཧతޡΓΛڭ͑Δ͜ͱ <> l ڭҭ FEVDBUJPO ɿֶߍڭҭΛ௨ͯ͡ӄ๳࿦ͱՊֶతࣄ࣮ͷ۠ผΛݟ෼͚ ΔೳྗΛ஁͑Δ͜ͱ <> From [23] [24] Lewandowsky, Stephan, and Sander Van Der Linden. "Countering misinformation and fake news through inoculation and prebunking." European Review of Social Psychology 32.2 (2021): 348- 384. [25] Dyer, Kathleen D., and Raymond E. Hall. "Effect of critical thinking education on epistemically unwarranted beliefs in college students." Research in Higher Education 60 (2019): 293-314.
51. 51 ݸਓʹର͢Δ཈੍ํ๏ɿ༧๷઀छ 
    ڭҭ ӄ๳࿦ͷӨڹͱͦͷରࡦ l ࠷΋ӄ๳࿦৴೦Λ௿Լͤ͞ΔՄೳੑ͕ߴ͍ͭͷ཈੍ํ๏ l ༧๷઀छʢJOGPSNBUJPO
    JOPDVMBUJPOʣɿӄ๳࿦઀৮લʹ๷ޚతͳೝ஌ε λϯεΛܗ੒͢ΔͨΊʹɺલ΋ͬͯӄ๳࿦ͷ࿦ཧతޡΓΛڭ͑Δ͜ͱ <> l ڭҭ FEVDBUJPO ɿֶߍڭҭΛ௨ͯ͡ӄ๳࿦ͱՊֶతࣄ࣮ͷ۠ผΛݟ෼͚ ΔೳྗΛ஁͑Δ͜ͱ <> From [23] ӄ๳࿦ʹ઀৮͢Δલʹ ରॲ͢Δ͜ͱ͕ॏཁʂ [24] Lewandowsky, Stephan, and Sander Van Der Linden. "Countering misinformation and fake news through inoculation and prebunking." European Review of Social Psychology 32.2 (2021): 348- 384. [25] Dyer, Kathleen D., and Raymond E. Hall. "Effect of critical thinking education on epistemically unwarranted beliefs in college students." Research in Higher Education 60 (2019): 293-314.
52. 52 ݸਓʹର͢Δ཈੍ํ๏ɿ༧๷઀छ 
    ڭҭ ӄ๳࿦ͷӨڹͱͦͷରࡦ ͡Ό͋ɺੈքதͷਓʑ ʹӄ๳࿦ʹؔ͢Δڭҭ ΍༧๷઀छΛ͢Ε͹ɺ ͜ͷ໰୊͸ղܾͩͶ
53. 53 ݸਓʹର͢Δ཈੍ํ๏ɿ༧๷઀छ 
    ڭҭ ӄ๳࿦ͷӨڹͱͦͷରࡦ ͡Ό͋ɺੈքதͷਓʑ ʹӄ๳࿦ʹؔ͢Δڭҭ ΍༧๷઀छΛ͢Ε͹ɺ ͜ͷ໰୊͸ղܾͩͶ ͓ۚͳ͍Αʁ
54. 54 ݸਓʹର͢Δ཈੍ํ๏ɿ༧๷઀छ 
    ڭҭ ӄ๳࿦ͷӨڹͱͦͷରࡦ ͡Ό͋ɺੈքதͷਓʑ ʹӄ๳࿦ʹؔ͢Δڭҭ ΍༧๷઀छΛ͢Ε͹ɺ ͜ͷ໰୊͸ղܾͩͶ ͓ۚͳ͍Αʁ l ༧๷઀छ΍ڭҭΛड͚ͤ͞Δର৅Λແࠩผ ʹܾΊΔͷͰ͸ͳ͘ɺޮՌͷߴ͍ର৅ʹ ߜͬͯߦ͏͜ͱ͕අ༻ରޮՌ͕ߴ͍ l ୭ʹɺͲͷλΠϛϯάͰɺͲͷΑ͏ͳํ๏ Ͱɺରॲ͢Δ΂͖͔Λߟ͑Δඞཁ
55. 55 ൃද಺༰  ιʔγϟϧϝσΟΞͱϑΣΠΫχϡʔε  ӄ๳࿦ͷӨڹͱͦͷରࡦ  ӄ๳࿦ରࡦͷର৅Λ୳͢ݚڀ
56. 56 ଟ͘ͷӄ๳࿦ݚڀϑϨʔϜϫʔΫ • ӄ๳࿦Λ৴͡Δߦҝʹ஫໨ • ϑΝΫτνΣοΫͳͲͷରࡦͷओཁλʔήοτ͸৴ͨ͡ਓ • ৴ͨ͡ਓ 
    ֦ࢄ͢Δਓɾߦಈ͢Δਓɺͱ͍͏ਤࣜͰٞ࿦ ͕ల։͞Ε͕ͪ ରࡦ
57. 57 ଟ͘ͷӄ๳࿦ݚڀϑϨʔϜϫʔΫ • ӄ๳࿦Λೝ஌ͨ͠ਓͷҰ෦͕৴͡Δɺ৴ͨ͡ਓͷҰ෦͕ ߦಈ͢Δͱ͍͏ɺஈ֊తͳϑϨʔϜϫʔΫͰଊ͑Δ • ೝ஌ɾ৴๬ɾߦಈΛҾ͖ى͜͢ཁҼΛͦΕͧΕ೺Ѳɻ • ͦΕͧΕͷஈ֊͝ͱʹ༗༻ͳհೖࡦΛద༻͢Δ͜ͱ͕ॏཁ ೝ஌ ৴೦ ߦಈ հೖࡦ հೖࡦ
58. 58 ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦ͷೝ஌ͷલ 陰謀論読者 過去に読んできた書籍 読書の傾向や好み ӄ๳࿦Λੵۃతʹೝ஌͢Δਓʑ͸ͲͷΑ͏ͳ৘ใΛ޷Ήͷ͔ʁ l ӄ๳࿦ʹؔ͢Δॻ੶ΛಡΜͩಡऀ͕ɺͲ͏͍ͬͨ܏޲ͷಡॻ Λߦ͓ͬͯΓɺաڈʹͲ͏͍ͬͨॻ੶ΛಡΜͰ͖͔ͨʁ
59. 59 ಡॻཤྺ͔Βӄ๳࿦܏౗ϢʔβΛൃݟɾ෼ੳ ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦ͷೝ஌ͷલ l ಡॻه࿥αʔϏεɿಡॻϝʔλʔ l ֤Ϣʔβ͕ʮ͍ͭʯɺʮԿͷຊʯΛͲͷΑ͏ͳײ૝Λ࣋ͬͯಡΜ͔ͩه࿥ l ӄ๳࿦ʹؔ͢ΔຊΛಡΜͩϢʔβͷཤྺ͕ݟΕΔ
60. 60 ಡॻཤྺσʔλͷ෼ੳ ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦ͷೝ஌ͷલ l ܭࢉػՊֶతΞϓϩʔνΛద༻Մೳͳܗʹม׵ 埋め込み表現 に変換 ベクトル表現 0.1, 0.3, 0.4, …, 0.9, 0.2, 0.4 0.2, 0.1, 0.3, …, 0.1, 0.0, 0.2 0.3, 0.5, 0.1, …, 0.0, 0.3, 0.5
61. 61 ຊͷҐஔ͚ͮͷՄࢹԽ ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦ͷೝ஌ͷલ
62. 62 ಛఆͷຊʢӄ๳࿦ʣʹ͍ۙຊͷൃݟ ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦ͷೝ஌ͷલ この本に似た本、 ってどんな本？ 近い本を推定
63. 63 ࠷ۙͷऔΓ૊Έ 
    ӄ๳࿦ͷೝ஌ͷલ 32
    ӄ๳࿦܏౗ಡऀʢλʔήοτϢʔβ܈ʣ͸ͲͷΑ͏ͳॻ੶Λ޷ΜͰಡΉ܏ ޲ʹ͋ΔͷͩΖ͏͔ʁ ωοτϫʔΫ ΫϥελϦϯά ࣌ؒܦա աڈͷಡॻཤྺ λʔήοτϢʔβ λʔήοτϢʔβ܈͕ӄ๳࿦ॻ੶ʹग़ձ͏·ͰʹಡΜͰ͖ͨຊ͔Βɼଞͷ Ϣʔβͱൺֱͯ͠ಛʹಡ·Ε͍ͯΔॻ੶ΫϥεΛݟ͚ͭΔ
64. 64 ࠷ۙͷऔΓ૊Έ 
    ӄ๳࿦ͷೝ஌ͷલ 32
    ӄ๳࿦܏౗ಡऀʢλʔήοτϢʔβ܈ʣ͸ͲͷΑ͏ͳॻ੶Λ޷ΜͰಡΉ܏ ޲ʹ͋ΔͷͩΖ͏͔ʁ
65. 65 ࠷ۙͷऔΓ૊Έ 
    ӄ๳࿦ͷೝ஌ͷલ 32
    ӄ๳࿦܏౗ಡऀʢλʔήοτϢʔβ܈ʣ͸ͲͷΑ͏ͳॻ੶Λ޷ΜͰಡΉ܏ ޲ʹ͋ΔͷͩΖ͏͔ʁ
66. 66 ࠷ۙͷऔΓ૊Έ 
    ӄ๳࿦ͷೝ஌ͷલ 32
    ӄ๳࿦܏౗ಡऀʢλʔήοτϢʔβ܈ʣ͸ͲͷΑ͏ͳॻ੶Λ޷ΜͰಡΉ܏ ޲ʹ͋ΔͷͩΖ͏͔ʁ
67. 67 32
    ӄ๳࿦܏౗ಡऀʢλʔήοτϢʔβ܈ʣ͸ͲͷΑ͏ͳॻ੶Λ޷ΜͰಡΉ܏ ޲ʹ͋ΔͷͩΖ͏͔ʁ ࠷ۙͷऔΓ૊Έ 
    ӄ๳࿦ͷೝ஌ͷલ
68. 68 32
    ӄ๳࿦܏౗ಡऀʢλʔήοτϢʔβ܈ʣ͸ͲͷΑ͏ͳॻ੶Λ޷ΜͰಡΉ܏ ޲ʹ͋ΔͷͩΖ͏͔ʁ ࠷ۙͷऔΓ૊Έ 
    ӄ๳࿦ͷೝ஌ͷલ
69. 69 32
    ӄ๳࿦܏౗ಡऀʢλʔήοτϢʔβ܈ʣ͸ͲͷΑ͏ͳॻ੶Λ޷ΜͰಡΉ܏ ޲ʹ͋ΔͷͩΖ͏͔ʁ ࠷ۙͷऔΓ૊Έ 
    ӄ๳࿦ͷೝ஌ͷલ ྺ࢙খઆɾεϐϦνϡΞϧॻɾϏδωεॻΛಡΜͰ͍ͨ܏޲
70. 70 ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦ͱͦͷ܏޲ 陰謀論ユーザ ⾏動に移す、移さない を分ける要因は？ ・質問票調査・サーベイ 暴動事件 啓蒙活動 静観 実際に⾏動 ӄ๳࿦΁ͷߦಈΛҾ͖ى͜͢܏޲΍ಛ௃͸ͳʹ͔ʁ
71. 71 ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦ͱͦͷ܏޲ ӄ๳࿦΁ͷߦಈΛҾ͖ى͜͢܏޲΍ಛ௃͸ͳʹ͔ʁ ೝ஌ ৴೦ ߦಈ ର৅ͷ੓࣏తࢥɾಛ௃ɾࣾձతଐੑ
72. 72 ࣭໰ྫ l ஍ٿԹஆԽ͸ՊֶऀʹΑΔͰͬͪ͋͛Ͱɺ࣮ࡍ͸஍ٿ͸ԹஆԽ͍ͯ͠ͳ͍ l ϫΫνϯͷ༗֐ͳ෭࡞༻͸ނҙʹެʹ͸Ӆ͞Ε͍ͯΔ l ੈքͷग़དྷࣄ΍ϧʔϧΛཪͰίϯτϩʔϧ͍ͯ͠ΔҰͭͷஂମ͕͋Δ l ࡏ೔֎ࠃਓ͕੓࣏Ո΍ϚείϛΛૢ͍ͬͯΔ l ೔ຊͰى͖ͨ͜Ε·Ͱͷେ͖ͳ஍਒͸ਓ޻஍਒Ͱ͋Δ l ώτܕᗡ஬ྨ͕ɺੈք֤ࠃͷࢦಋऀͱͳΓਓྨΛࢧ഑ͯ͠ l ৽ܕίϩφ΢Πϧε͸࣮ࡍʹ͸ଘࡏ l ਓྨ͸طʹӉ஦ਓͱ઀৮͍ͯ͠Δ͕͜ͷࣄ࣮͸Ӆ͞Εͯ l ̕ɽ̍̍ถࠃಉ࣌ଟൃςϩࣄ݅ʹ͸ɺถࠃ੓෎͕ؔ༩͍ͯ͠Δ l ̎̌̎̌೥ͷถࠃେ౷ྖબڍʹ͓͍ͯ͸όΠσϯਞӦʹબڍෆਖ਼͕͋ͬͨ l ੓෎͕ඈߦػӢͰ༗֐෺࣭Λۭ͔Βࢄ෍͍ͯ͠ΔʢέϜτϨΠϧʣ ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦ͱͦͷ܏޲
73. 73 ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦ͱͦͷ܏޲ l ೔ຊͱΞϝϦΧɺͦΕͧΕ ݅ͣͭαϯϓϧΛऔಘ l ֦ࢄߦಈɿ৘ใൃ৴΍৘ใڞ༗Λ͔ͨ͠ʁ l ࣔҖߦಈɿू·ΓʹࢀՃͨ͠Γޱ࿦ʹͳ͔ͬͨʁ
74. 74 ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦ͱͦͷ܏޲ l ӄ๳࿦Λʮ஌Δʯ͜ͱʹڧ͍ཁҼ
75. 75 ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦ͱͦͷ܏޲ l ӄ๳࿦Λʮ৴͡Δʯ͜ͱʹڧ͍ཁҼ
76. 76 ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦ͱͦͷ܏޲ l ӄ๳࿦Λʮ֦ࢄ͢Δʯ͜ͱʹڧ͍ཁҼ
77. 77 ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦ͱͦͷ܏޲ l ӄ๳࿦ʹؔͯ͠ʮߦಈ͢Δʯ͜ͱʹڧ͍ཁҼ
78. 78 ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦৴೦ʹର͢Δରࡦ ӄ๳࿦΁ͷ৴೦ʹ༗ޮͳख़ྀೳྗΛ--.Ͱ޲্Ͱ͖Δ͔ʁ $PHOJUJWF
    3FGMFDUJPO
    5FTU
    ਓ͕௚ײతͰ҆қͳ౴͑Λ৐Γӽ͑ɺ ΑΓਂ͘ख़ߟͯ͠ਖ਼͍͠౴͑Λಋ͖ग़͢ೳྗ΍܏޲Λଌఆ͢ΔͨΊ ʹઃܭ͞Εͨ৺ཧςετ • ބʹεΠϨϯͷ༿͕ු͔ΜͰ͓Γɺͦͷ໘ੵ͸ຖ೔ഒʹ૿͑· ͢ɻ೔ޙʹބશମΛ෴͏ͱ͢Δͱɺބͷ൒෼Λ෴͏ͷʹԿ೔ ͔͔ΔͰ͠ΐ͏͔ʁ • ଠ࿠ͷ෕਌ʹ͸ਓͷଉࢠ͕͍·͢ɻਓ໨͸Ұ࿠ɺਓ໨͸ೋ ࿠Ͱ͢ɻਓ໨ͷଉࢠͷ໊લ͸ԿͰ͠ΐ͏ʁ
79. 79 ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦৴೦ʹର͢Δରࡦ ӄ๳࿦΁ͷ৴೦ʹ༗ޮͳख़ྀೳྗΛ--.Ͱ޲্Ͱ͖Δ͔ʁ $35 4DPSF հೖલ ର࿩ٞ࿦ $35 4DPSF հೖޙ l $PHOJUJWF
    3FGMFDUJPOೳྗ͸ӄ๳࿦ͷ৴೦ʹ༗ޮ l $PHOJUJWF
    3FMFDUJPOೳྗΛ--.ͱͷର࿩Ͱ༰қʹ޲্Ͱ͖Δ͔ʁ
80. 80 ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦৴೦ʹର͢Δରࡦ ӄ๳࿦΁ͷ৴೦ʹ༗ޮͳख़ྀೳྗΛ--.Ͱ޲্Ͱ͖Δ͔ʁ l ৚݅ɿ೔ৗձ࿩ʢίϯτϩʔϧʣ
    l ৚݅ɿ౴͑Λ௚઀ఏࣔ
    l ৚݅ɿ࣭໰Ͱख़ߟΛଅ͢
    l ৚݅ɿৼΓฦΓͰɺώϯτΛఏࣔ
81. 81 ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦৴೦ʹର͢Δରࡦ ӄ๳࿦΁ͷ৴೦ʹ༗ޮͳख़ྀೳྗΛ--.Ͱ޲্Ͱ͖Δ͔ʁ l ৚݅ɿ೔ৗձ࿩ʢίϯτϩʔϧʣ
    l ৚݅ɿ౴͑Λ௚઀ఏࣔ
    l ৚݅ɿ࣭໰Ͱख़ߟΛଅ͢
    l ৚݅ɿৼΓฦΓͰɺώϯτΛఏࣔ ৚݅ ৚݅ ৚݅ ৚݅ հೖલ հೖޙ հೖલ հೖޙ հೖલ հೖޙ հೖલ հೖޙ
82. 82 ࠷ۙͷऔΓ૊Έ
    ӄ๳࿦৴೦ʹର͢Δରࡦ ӄ๳࿦΁ͷ৴೦ʹ༗ޮͳख़ྀೳྗΛ--.Ͱ޲্Ͱ͖Δ͔ʁ l ৚݅ɿ೔ৗձ࿩ʢίϯτϩʔϧʣ
    l ৚݅ɿ౴͑Λ௚઀ఏࣔ
    l ৚݅ɿ࣭໰Ͱख़ߟΛଅ͢
    l ৚݅ɿৼΓฦΓͰɺώϯτΛఏࣔ ৚݅ ৚݅ ৚݅ ৚݅ հೖલ հೖޙ հೖલ հೖޙ հೖલ հೖޙ հೖલ հೖޙ ৚݅Ͱ͸հೖޙʹ$35είΞ͕ ༗ҙʹ্ঢ
    ର࿩Ͱʮ࿅श໰୊ʯΛٻΊͨඃݧऀ ͷείΞ͕ಛʹ޲্
83. 83 l ݹయతͳʮ༗֐৘ใݕग़ʯͷݚڀ͸ݮগ܏޲ l ৽͍͠༗֐৘ใͷग़ݱͱͷΠλνͬ͜͝Ͱඅ༻ରޮՌ͕௿͍ l ݕग़ݚڀ͸ɺԠ༻΍࣮૷ͷஈ֊ʹҠߦʢ ৴པੑɾઆ໌ੑʣ l ͦͷҰํͰɺհೖɾ཈੍ɾ๷ޚͷ؍఺ͷݚڀ͕૿Ճɻ l ༗֐৘ใΛ৴๬ͨ͠ਓʑʹରͯ͠༗ޮͳରࡦ l %FCVOLJOH
    
    1SFCVOLJOH l จ຺ʹԠͨ͡ϝοηʔδੜ੒΍հೖࡦͱͯ͠--.ͷ׆༻͕૿Ճ ޡ৘ใɾӄ๳࿦ͷࠓޙʹ͍ͭͯ ޡ৘ใɾӄ๳࿦ݚڀ͸Ͳ͜ʹߦ͘ͷ͔ʁ
84. 84 l ޡ৘ใɾӄ๳࿦͔ΒφϥςΟϒ΁ l ޡ৘ใ͸൱ఆͰ͖Δ͕ɺӄ๳࿦͸൱ఆͰ͖ͳ͍ l ӄ๳࿦Λ৴͡Δ͜ͱ͸ݸਓͷࣗ༝ʢ಺৺ͷࣗ༝ʣ l ୭͕ɺͲͷج४ͰɺͲͷΑ͏ʹɺհೖ͢Δͷ͔ʁ୭͕ͦͷίετΛࢧ෷͏ͷ ͔ʁ l ͭͷޡ৘ใɾӄ๳࿦Λ൱ఆͨ͠ͱ͜ΖͰ৴ͯ͡Δਓ͸ผͷཧ༝͔Βͦͷ෺ ޠΛ৴͡ଓ͚Δ l ෳ਺ͷޡ৘ใɺਅِෆ໌ͷ৘ใɺਖ਼͍͠৘ใͳͲ༷ʑͳஅยʹΑͬ ͯߏ੒͞ΕΔʮφϥςΟϒʯͱʮφϥςΟϒʯͷରཱͱͯ͠ੈքΛ ଊ͑Δ࣌୅ʁ ޡ৘ใɾӄ๳࿦ͷࠓޙʹ͍ͭͯ ޡ৘ใɾӄ๳࿦ݚڀ͸Ͳ͜ʹߦ͘ͷ͔ʁ
85. 85 l ޡ৘ใɾӄ๳࿦͔ΒφϥςΟϒ΁ l ޡ৘ใ͸൱ఆͰ͖Δ͕ɺӄ๳࿦͸൱ఆͰ͖ͳ͍ l ӄ๳࿦Λ৴͡Δ͜ͱ͸ݸਓͷࣗ༝ʢ಺৺ͷࣗ༝ʣ l ୭͕ɺͲͷج४ͰɺͲͷΑ͏ʹɺհೖ͢Δͷ͔ʁ୭͕ͦͷίετΛࢧ෷͏ͷ ͔ʁ l ͭͷޡ৘ใɾӄ๳࿦Λ൱ఆͨ͠ͱ͜ΖͰ৴ͯ͡Δਓ͸ผͷཧ༝͔Βͦͷ෺ ޠΛ৴͡ଓ͚Δ l ෳ਺ͷޡ৘ใɺਅِෆ໌ͷ৘ใɺਖ਼͍͠৘ใͳͲ༷ʑͳஅยʹΑͬ ͯߏ੒͞ΕΔʮφϥςΟϒʯͱʮφϥςΟϒʯͷରཱͱͯ͠ੈքΛ ଊ͑Δ࣌୅ʁ ޡ৘ใɾӄ๳࿦ͷࠓޙʹ͍ͭͯ ޡ৘ใɾӄ๳࿦ݚڀ͸Ͳ͜ʹߦ͘ͷ͔ʁ ʮφϥςΟϒʯͱ͸ͳʹ͔ʁ ʮφϥςΟϒʯΛऔΓѻ͏ݚڀΛߦ͍͍ͨ
86. 86 l ૝૾ྗʹΑͬͯՃ଎͞Εͨࣗવબ୒ l ݪҼ͔Β݁ՌΛਪଌɾҟͳΔߦಈͷϧʔϧ ͷ݁ՌΛͦΕͧΕ༧ଌ l ԾઆɾՄೳੑɻ൓࣮తࢥߟɺى͜ΓಘΔ͜ ͱΛ৺ͷதͰϞσϧԽ ޡ৘ใɾӄ๳࿦ͷࠓޙʹ͍ͭͯ φϥςΟϒೳྗʢ෺ޠࢥߟʣͱ͸ʁ Fletcher, Angus. Storythinking: The new science of narrative intelligence. Columbia University Press, 2023.
87. 87 l ݸਓɾूஂͷΞΠσϯςΟςΟΛφϥςΟϒͰߏங l φϥςΟϒతͳ൓࣮Ծ૝͕ɺ੓࣏తରཱ΍ࠃࡍฆ૪ͷਖ਼౰Խʹ༻ ͍ΒΕΔ৔߹ l ྫɿυϛϊཧ࿦ʢϕτφϜઓ૪ʣɿ͋Δ஍ҬͰڞ࢈ओ͕֦ٛେ͢Δͱɺυ ϛϊ౗͠ͷΑ͏ʹྡ઀͢Δࠃʑ΋࣍ʑͱڞ࢈ओٛԽ͢Δ͔΋͠Εͳ͍ l ྫɿΠϥΫઓ૪ l ࣾձӡಈʹ͓͍ͯφϥςΟϒ͸ಈһྗͱͳΔ ޡ৘ใɾӄ๳࿦ͷࠓޙʹ͍ͭͯ φϥςΟϒ͸ରཱΛੜΈग़͢
88. 88 l ౤ߘσʔλ͔Βɺओޠड़ޠ໨తޠͷτϦϓϨοτΛநग़ ޡ৘ใɾӄ๳࿦ͷࠓޙʹ͍ͭͯ φϥςΟϒΛऔΓग़͢ݚڀྫɿࣗಈநग़ Zhao, Wanying, et al. "Discovering collective narratives shifts in online discussions." Proceedings of the International AAAI Conference on Web and Social Media. Vol. 18. 2024.
89. 89 l 3FEEJUσʔλ͔ΒਓखͰφϥ ςΟϒσʔληοτΛߏங l ֶशࡁΈϞσϧΛ'JOFUVOJOH͠ ɺӄ๳࿦ʹؔ͢ΔφϥςΟϒ෼ ྨػΛߏங ޡ৘ใɾӄ๳࿦ͷࠓޙʹ͍ͭͯ φϥςΟϒΛऔΓग़͢ݚڀྫɿ෼ྨػͷߏங Diab, Ahmad, Rr Nefriana, and Yu-Ru Lin. "Classifying conspiratorial narratives at scale: False alarms and erroneous connections." Proceedings of the International AAAI Conference on Web and Social Media. Vol. 18. 2024.
90. 90 l ݱঢ়ͷٕज़ͰʮφϥςΟϒʯΛऔΓग़ͤΔͱ͸ݴ͑ͳ͍ l ͦ΋ͦ΋σʔλ͔ΒऔΓग़ͤΔʮφϥςΟϒʯͱ͸ʁ φϥςΟϒΛͲͷΑ͏ͳ୯ҐͰߟ͑Δ͔ʁ l Ұͭͷग़དྷࣄʹରͯ͠ෳ਺ͷղऍ΍෺ޠ͕ฒߦͯ͠ൃੜ ͲͷΑ͏ʹ෼཭͢Δͷ͔ʁ l ʮจ຺ʯ͕ॏࢹ͞ΕΔ͕ɺจ຺Λਖ਼֬ʹଊ͑Δ͜ͱ͕Ͱ͖Δͷ ͔ʁ ޡ৘ใɾӄ๳࿦ͷࠓޙʹ͍ͭͯ φϥςΟϒநग़ͷ՝୊
91. 91 l طଘͷݚڀͰॏཁࢹ͞Ε͖ͯͨɺ࿦ཧೳྗ͚ͩͰͳ͘ɺφϥςΟ ϒೳྗ΋஁͑Δඞཁ͕͋ΔͷͰ͸ʁ l ݱ୅ͷ৘ใ͸ਖ਼͍ؒ͠ҧ͍ͱ͍͏͚ͩͰͳ͘ɺؒҧ͍ͱ͸ݴ͑ͳ͍͕ ʮັྗతφϥςΟϒʯͱ֦ͯ͠ࢄ͞ΕΔঢ়گ l ʮφϥςΟϒʯΛ၆ᛌతʹཧղ͢Δೳྗ l ༩͑ΒΕͨ৘ใ͔ΒҼՌ΍෺ޠߏ଄Λཧղ l ଟ༷ͳφϥςΟϒʹ଱ੑΛ࣋ͭೳྗ l ෳ਺ͷετʔϦʔΛฒߦͯ͠ଊ͑ɺ͜Ε͸Ұͭͷݟํʹա͗ͳ͍ͱ૬ରԽ Ͱ͖Δೳྗ ޡ৘ใɾӄ๳࿦ͷࠓޙʹ͍ͭͯ φϥςΟϒͱ༗֐৘ใ