Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations | Paper Citation Record

Observation e8b8a86c-bb77-45da-addc-2fd3f1c04f34 · outbound

This paper cites Acting the part: Examining information operations within #BlackLivesMatter discourse.Proceedings of the ACM on Human-Computer Interaction (CSCW), 2:1–27, 2018.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Acting the part: Examining information operations within #BlackLivesMatter discourse.Proceedings of the ACM on Human-Computer Interaction (CSCW), 2:1–27, 2018

Reference 1

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Observation 3b4e6e6d-947f-4675-8c15-1f65d6fb45f4 · outbound

This paper cites Analyzing the digital traces of political manipulation: The 2016 Russian interference Twitter campaign.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Analyzing the digital traces of political manipulation: The 2016 Russian interference Twitter campaign

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Observation 51af5b34-f8eb-47cc-889e-30cdc02e8ed6 · outbound

This paper cites A unified taxonomy of harmful content.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations A unified taxonomy of harmful content

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Observation 693276f7-4aab-48cf-a6b1-1f578365bf30 · outbound

This paper cites Brady, Julian A.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Brady, Julian A

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Observation 36c7be3a-0230-4251-9f0e-34a65c2d6b28 · outbound

This paper cites Dealing with disagreements: Looking beyond the majority vote in subjective an- notations.Transactions of the Association for Com- putational Linguistics (TACL), 10:92–110, 2022.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Dealing with disagreements: Looking beyond the majority vote in subjective an- notations.Transactions of the Association for Com- putational Linguistics (TACL), 10:92–110, 2022

Reference 5

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Observation c92f50ba-98be-4293-9e12-d34852b975c3 · outbound

This paper cites Automated hate speech detection and the problem of offensive language.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Automated hate speech detection and the problem of offensive language

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Observation 7ead9f57-80dc-4984-a76f-a398dc5eb564 · outbound

This paper cites Latent hatred: A benchmark for understanding implicit hate speech.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Latent hatred: A benchmark for understanding implicit hate speech

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Observation 5b166828-0808-4563-8c23-ebcc3fd48a88 · outbound

This paper cites Cultural Targets, Structural Frames, Binding Morals: A Cross-Lingual Audit of Online Hate in Multicultural Singapore.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Cultural Targets, Structural Frames, Binding Morals: A Cross-Lingual Audit of Online Hate in Multicultural Singapore

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Observation 956b9c5c-72c9-4d4b-9839-88442e242c69 · outbound

This paper cites Five myths about influence oper- ations: What 25 million tweets across seven state campaigns reveal.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Five myths about influence oper- ations: What 25 million tweets across seven state campaigns reveal

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Observation 0d4b7ede-62f5-4c92-9588-845a24f8974e · outbound

This paper cites Characterizing social media manipulation in the 2020 U.S.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Characterizing social media manipulation in the 2020 U.S

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Observation 884cb9dd-e68c-4fa0-b884-24a8d9cad5f3 · outbound

This paper cites Finkel, Christopher A.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Finkel, Christopher A

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Observation 7bf1881c-2714-442e-83cb-7f41437d80e0 · outbound

This paper cites Russian troll tweets.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Russian troll tweets

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Observation 85ac9a05-66ae-435e-b041-6e60d40849b7 · outbound

This paper cites A survey on auto- matic detection of hate speech in text.ACM Com- puting Surveys, 51(4):1–30, 2018.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations A survey on auto- matic detection of hate speech in text.ACM Com- puting Surveys, 51(4):1–30, 2018

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Observation 4c6a53d5-d7dc-4b7d-beda-96f22a2fecaf · outbound

This paper cites Toxic, hateful, offensive or abusive? what are we really classifying? an empirical analysis of hate speech datasets.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Toxic, hateful, offensive or abusive? what are we really classifying? an empirical analysis of hate speech datasets

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Observation 589e5005-aec9-406e-b626-802dcfbdc12d · outbound

This paper cites Large scale crowd- sourcing and characterization of Twitter abusive be- havior.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Large scale crowd- sourcing and characterization of Twitter abusive be- havior

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Observation 288e1fd1-0f0a-49ca-874b-ef73a0472e9b · outbound

This paper cites Black trolls matter: Racial and ideological asymme- tries in social media disinformation.Social Science Computer Review, 40(3):560–578, 2022.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Black trolls matter: Racial and ideological asymme- tries in social media disinformation.Social Science Computer Review, 40(3):560–578, 2022

Reference 16

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Observation 7e4b1882-ab46-4b37-ab07-8e7f7c9aebfa · outbound

This paper cites Frimer, Reihane Boghrati, Jonathan Haidt, Jesse Graham, and Morteza Dehghani.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Frimer, Reihane Boghrati, Jonathan Haidt, Jesse Graham, and Morteza Dehghani

Reference 17

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Observation 29c81d57-a27d-4440-99dc-cd19f3e18cf7 · outbound

This paper cites Position: RLHF may not reflect genuine preferences.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Position: RLHF may not reflect genuine preferences

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This paper cites ChatGPT outperforms crowd workers for text-annotation tasks.Proceedings of the National Academy of Sciences, 120(30):e2305016120, 2023.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations ChatGPT outperforms crowd workers for text-annotation tasks.Proceedings of the National Academy of Sciences, 120(30):e2305016120, 2023

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This paper cites an unresolved cited work.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Unresolved cited work

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Observation c38ab4bf-caf8-4654-85ec-a056d678c079 · outbound

This paper cites Still out there: Modeling and identifying Russian troll accounts on Twitter.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Still out there: Modeling and identifying Russian troll accounts on Twitter

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Observation 7399f630-7734-49c3-81da-28481dc2fd2c · outbound

This paper cites Westwood.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Westwood

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Observation 8b9b5be8-d0f5-4d4a-b3dd-125c0ae26805 · outbound

This paper cites Jacobs and Hanna Wallach.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Jacobs and Hanna Wallach

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This paper cites Retweet- BERT: Political leaning detection using language features and information diffusion on social networks.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Retweet- BERT: Political leaning detection using language features and information diffusion on social networks

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Observation 61a94960-4819-49c1-bc44-1b373a097549 · outbound

This paper cites Reliability in content analy- sis: Some common misconceptions and recommenda- tions.Human Communication Research, 30(3):411– 433, 2004.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Reliability in content analy- sis: Some common misconceptions and recommenda- tions.Human Communication Research, 30(3):411– 433, 2004

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Observation 56e2593c-4391-4d90-8fd0-b1a0122b1ea6 · outbound

This paper cites Watch your language: Investigating content moderation with large language models.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Watch your language: Investigating content moderation with large language models

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Observation ed788957-9818-4b60-a3ad-65f9e9ab9ef3 · outbound

This paper cites Linvill and Patrick L.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Linvill and Patrick L

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Observation 9ce811f1-e2d5-4900-bd82-5b7bca4886f5 · outbound

This paper cites Creating a general Russian sentiment lexicon.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Creating a general Russian sentiment lexicon

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This paper cites University of Chicago Press, Chicago, IL, 2018.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations University of Chicago Press, Chicago, IL, 2018

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This paper cites From dogwhistles to bullhorns: Unveil- ing coded rhetoric with language models.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations From dogwhistles to bullhorns: Unveil- ing coded rhetoric with language models

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Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Mohammad and Peter D

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This paper cites Carley.Bots, Bias, and Influence: The Hidden Architects of Social Media.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Carley.Bots, Bias, and Influence: The Hidden Architects of Social Media

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This paper cites Keeping humans in the loop: Human-centered automated annotation with generative AI.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Keeping humans in the loop: Human-centered automated annotation with generative AI

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This paper cites Pennebaker, Ryan L.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Pennebaker, Ryan L

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This paper cites The “problem” of human label vari- ation: On ground truth in data, modeling and eval- uation.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations The “problem” of human label vari- ation: On ground truth in data, modeling and eval- uation

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This paper cites Measuring bot and human behavioral dynamics.Frontiers in Physics, 8:125, 2020.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Measuring bot and human behavioral dynamics.Frontiers in Physics, 8:125, 2020

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This paper cites Van Bavel, and Sander van der Linden.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Van Bavel, and Sander van der Linden

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This paper cites Beyond incivility: Understanding patterns of uncivil and intolerant discourse in online political talk.Communication Research, 49(3):399– 425, 2022.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Beyond incivility: Understanding patterns of uncivil and intolerant discourse in online political talk.Communication Research, 49(3):399– 425, 2022

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This paper cites XSTest: A test suite for identifying exaggerated safety behaviours in large language models.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations XSTest: A test suite for identifying exaggerated safety behaviours in large language models

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This paper cites Unrav- eling the web of disinformation: Exploring the larger context of state-sponsored influence campaigns on Twitter.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Unrav- eling the web of disinformation: Exploring the larger context of state-sponsored influence campaigns on Twitter

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This paper cites short is the road that leads from fear to hate.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations short is the road that leads from fear to hate

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Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Unresolved cited work

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Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Unresolved cited work

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This paper cites Nwala, Lake Yin, Luca Luceri, Alessandro Flammini, and Filippo Menczer.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Nwala, Lake Yin, Luca Luceri, Alessandro Flammini, and Filippo Menczer

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Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations The Language of Influence: Sentiment, Emotion, and Hate Speech in State Sponsored Influence Operations

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Observation f51d6c1f-8dcd-429d-b3d4-cebd17903a08 · outbound

This paper cites Toxicity in state sponsored information operations.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Toxicity in state sponsored information operations

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Observation 0fdca672-d683-4738-939b-ffd9d61e72df · outbound

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Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Disinformation’s spread: Bots, trolls and all of us.Nature, 571(7766):449, 2019

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This paper cites Bots increase exposure to negative and inflammatory content in online social systems.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Bots increase exposure to negative and inflammatory content in online social systems

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Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Temporal dynamics of co- ordinated online behavior: Stability, archetypes, and influence.Proceedings of the National Academy of Sciences, 121(20):e2307038121, 2024

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This paper cites Uma, Tommaso Fornaciari, Dirk Hovy, Silviu Paun, Barbara Plank, and Massimo Poesio.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Uma, Tommaso Fornaciari, Dirk Hovy, Silviu Paun, Barbara Plank, and Massimo Poesio

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Observation bf586e7b-cbc5-4c62-b545-7a731ef27d9f · outbound

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Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Directions in abusive language training data: A systematic review of garbage in, garbage out.PLOS ONE, 15(12):e0243300, 2020

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Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Evidence of inter-state coordination amongst state-backed information operations.Scien- tific Reports, 13:7716, 2023

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This paper cites Understanding abuse: A typology of abusive language detection subtasks.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Understanding abuse: A typology of abusive language detection subtasks

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Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Hateful symbols or hateful people? predictive features for hate speech detection on Twitter

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Observation 497c12fa-0143-47eb-b2ae-46cfa5984b41 · outbound

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Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Disinformation warfare: Understanding state-sponsored trolls on Twitter and their influence on the web

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This paper cites Who let the trolls out? towards under- standing state-sponsored trolls.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Who let the trolls out? towards under- standing state-sponsored trolls

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This paper cites Can large lan- guage models transform computational social science? Computational Linguistics, 50(1):237–291, 2024.

Manufactured Divisiveness: Decomposing the Hostile Content of Seven Social Media Influence Operations Can large lan- guage models transform computational social science? Computational Linguistics, 50(1):237–291, 2024

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