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Auditing Recommender Systems. Overview Of Existing Audits, Risk Assessments and Studies on Potential "VLOPs". Date: 30.03.2024
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Would you like to carry out an audit or risk assessment on recommender systems of potential VLOPs, but do not know how to proceed? Following the framework of Meßmer & Degeling 2023*, this mapping provides an overview of existing audits, risk assessments and studies.
This document thereby only provides an overview of existing research. The assessment of the quality and content of the respective studies is the responsibility of the user.
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*Meßmer & Degeling (2023). Auditing Recommender Systems. Putting the DSA into practice with a risk-scenario-based approach. Stiftung Neue Verantwortung. https://www.stiftung-nv.de/de/publication/auditing-recommender-systems
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Alexander Hohlfeld
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AuthorsYearStudyPlatformAudit TypeRisksForm of AuditForm of Audit II Elements of the Platform
Elements of the Platform II
Link
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Freelon et al.2024
What's in your PIE? Understanding the contents of personalized information environments with PIEGraph
TwitterThird-PartyBias; MisinformationCrowdsourced; Survey-User Experience; Algorithmic LogicRecSyshttps://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24869
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de Mello et al.2024
Twitter (X) use predicts substantial changes in well-being, polarization, sense of belonging, and outrage
TwitterThird-partyWell-Being; PolarisationCrowdsourced; Survey-User Experiene-https://www.nature.com/articles/s44271-024-00062-z#peer-review
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Vombatkere et al.2024
TikTok and the Art of Personalization: Investigating Exploration and Exploitation on Social Media Feeds
TikTokThird-party-
Automated; Crowdsourced
SockPuppetAlgorithmic LogicRecSyshttps://kvombatkere.github.io/assets/TikTok_Paper_WebConf24.pdf
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Crossover2024
"UP NEXT", BIASED POLITICS? Youtube Recommendations and Political Bias in the Finnish President Election 2024
YouTubeThird-partyBiasAutomatedScrapingAlgorithmic LogicRecSyshttps://crossover.social/finnish-far-right-videos-highly-recommended-by-youtube-during-the-presidential-race/
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Renault et al.2024Collaboratively adding context to social media posts reduces the sharing of false newsTwitterThird-partyDisinformationAutomatedAPIContent Moderation-https://arxiv.org/abs/2404.02803
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AI Forensics & Check First2023
The Amazing Library: An Analysis of Amazon´s Bookstore Algorithms within the DSA Framework
AmazonThird-PartyDisinformation; Rabbit HoleAutomatedScrapingAlgorithmicLogicRecSyshttps://checkfirst.network/the-amazing-library/
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Algorithm Watch & AI Forensics
2023Generative AI and elections: Are chatbots a reliable source of information for voters?BingThird-PartyMisinformationAutomatedScrapinghttps://algorithmwatch.org/en/study-microsofts-bing-chat/
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Ali et al.2023Problematic Advertising and its Disparate Exposure on FacebookFacebookThird-PartyBiasSurvey; Crowdsourced-Advertisement, Algorithmic Logic-https://arxiv.org/abs/2306.06052
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Amnesty International2023
Driven Into The Darkness. How Tiktok's ‘For You’ Feed Encourages Self-Harm And Suicidal Ideation
TikTokThird-PartyMental HealthSurvey; AutomatedSockPuppetAlgorithmicLogicRecSyshttps://www.amnesty.org/en/documents/POL40/7350/2023/en/
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Amnesty International2023“I Feel Exposed” Caught In Tiktok’s Surveillance WebTikTokThird-PartyPrivacy; Protection of MinorsDocument; Survey-Data related practices-https://www.amnesty.org/en/documents/POL40/7349/2023/en/
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Bouchaud et al.2023Crowdsourced audit of Twitter’s recommender systemsTwitterThird-PartyBias
Automated; Crowdsourced
APIAlgorithmic LogicRecSyshttps://www.nature.com/articles/s41598-023-43980-4
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Council for Media Services (CMS)
2023
The prevalence of harmful or potentially illegal content on digital platforms following the Bratislava terrorist attack
Facebook; YouTube; Instagram; TikTok
Third-PartyIllegal ContentScraping-Content Moderation; Report Mechanisms-
https://www.epra.org/news_items/the-role-of-online-platforms-in-harmful-content-slovak-regulator-investigates-user-s-report-mechanisms
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Eady et al.2023
Exposure to the Russian Internet Research Agency foreign influence campaign on Twitter in the 2016 US election and its relationship to attitudes and voting behavior
TwitterThird-partyDisinformationCrowdsourced; Survey-User Experience-https://www.nature.com/articles/s41467-022-35576-9
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European Commission2023
Digital Services Act. Application of the risk management framework to Russian disinformation campaigns
Facebook; YouTube; Instagram; TikTok; Telegram
Third-PartyDisinformation
Automated; Document
APIContent Moderation; Algorithmic LogicRecSys
https://op.europa.eu/en/publication-detail/-/publication/c1d645d0-42f5-11ee-a8b8-01aa75ed71a1/language-en
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González-Bailón et al.2023Asymmetric ideological segregation in exposure to political news on FacebookFacebookSecond-partyPolarisationData-User Experience-https://www.science.org/doi/full/10.1126/science.ade7138
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Guess et al.2023
How do social media feed algorithms affect attitudes and behavior in an election campaign?
FacebookSecond-partyElectoral RisksArchitecture-User Experience; Algorithmic LogicRecSyshttps://www.science.org/doi/full/10.1126/science.abp9364
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Guess et al.2023
Reshares on social media amplify political news but do not detectably affect beliefs or opinions
FacebookSecond-partyPolarisationArchitecture-User Experience; Algorithmic LogicRecSyshttps://www.science.org/doi/full/10.1126/science.add8424
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Hagar & Diakopoulos2023Algorithmic indifference: The dearth of news recommendations on TikTokTikTokThird-Party-AutomatedSockPuppetAlgorithmic LogicRecSyshttps://journals.sagepub.com/doi/full/10.1177/14614448231192964
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Haroon et al.2023
Auditing YouTube’s recommendation system for ideologically congenial, extreme, and problematic recommendations
YouTubeThird-PartyRabbit HoleAutomatedSockPuppetAlgorithmicLogicRecSyshttps://www.pnas.org/doi/10.1073/pnas.2213020120
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Hosseinmardi et al.2023
Causally estimating the effect of YouTube’s recommender system using counterfactual bots
YouTubeThird-Party-AutomatedSockPuppetAlgorithmicLogicRecSyshttps://arxiv.org/abs/2308.10398
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Human Rights Watch2023
Meta’s Broken Promises: Systemic Censorship of Palestine Content on Instagram and Facebook
Instagram; Facebook
Third-PartyCensorship; ShadowBanningSurvey; Crowdsourced-Content Moderation-https://www.hrw.org/news/2023/12/20/meta-systemic-censorship-palestine-content
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Ibrahim et al. 2023YouTube’s recommendation algorithm is left-leaning in the United StatesYouTubeThird-PartyBiasAutomatedSockPuppetAlgorithmic LogicRecSyshttps://academic.oup.com/pnasnexus/article/2/8/pgad264/7242446?login=false
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Liu et al.2023How to Train Your YouTube Recommender to Avoid Unwanted VideosYouTubeThird-PartyUnwanted ContentAutomated; SurveySock PuppetAlgorithmic Logic; User InterfaceRecSyshttps://arxiv.org/abs/2307.14551
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Liu et al.2023
Algorithmic recommendations have limited effects on polarization: A naturalistic experiment on YouTube
YouTubeThird-PartyPolarizationSurvey; Crowdsourced-AlgorithmicLogicRecSyshttps://dcknox.github.io/files/LiuEtAl_AlgoRecsLimitedPolarizationYouTube.pdf
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Miller et al.2023Antisemitism on Twitter Before and After Elon Musk’s AcquisitionTwitterThird-partyHateSpeechAutomatedAPIContent Moderation-https://beamdisinfo.org/deployments/antisemitism-on-twitter-before-and-after-elon-musks-acquisition/
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Milli et al. 2023Twitter's Algorithm: Amplifying Anger, Animosity, and Affective PolarizationTwitterThird-partyPolarisationSurvey; Crowdsourced-Algorithmic Logic; User ExperienceRecSyshttps://arxiv.org/abs/2305.16941
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Milton et al.2023“I See Me Here”: Mental Health Content, Community, and Algorithmic Curation on TikTokTikTokThird-partyMental HealthSurvey-Algorithmic Logic; Content ModerationRecSys
https://cse.umn.edu/college/news/how-tiktok-affecting-our-mental-health-its-complicated-new-u-m-study-shows
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Nechushtai et al.2023
More of the Same? Homogenization in News Recommendations When Users Search on Google, YouTube, Facebook, and Twitter
YouTube; Facebook; Twitter; Google
Third-partyFilterbubbleCrowdsourced-Algorithmic LogicRecSyshttps://www.tandfonline.com/doi/full/10.1080/15205436.2023.2173609?journalCode=hmcs20
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Network Contagion Research Institute & Rutgers University Miller Center
2023
A Tik-Tok-ing Timebomb: How TikTok’s Global Platform Anomalies Align with the Chinese Communist Party’s Geostrategic Objectives
TikTokThird-PartyCensorship; ShadowBanningAutomatedScrapingAlgorithmicLogicRecSys
https://networkcontagion.us/reports/12-21-23-a-tik-tok-in-timebomb-how-tiktoks-global-platform-anomalies-align-with-the-chinese-communist-partys-geostrategic-objectives/
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Nyhan et al.2023Like-minded sources on Facebook are prevalent but not polarizingFacebookSecond-partyPolarisationArchitecture-Algorithmic LogicRecSyshttps://www.nature.com/articles/s41586-023-06297-w
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Panoptykon Foundation2023
Algorithms of Trauma #2 Stuck in a “doomscrolling trap” on Facebook? The platform will not let you escape
FacebookThird-PartyMental HealthAutomatedSockPuppetAlgorithmicLogic; User InterfaceRecSyshttps://en.panoptykon.org/algorithms-of-trauma-2-anxious-about-health
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Robertson et al. 2023
Users choose to engage with more partisan news than they are exposed to on Google Search
GoogleThird-partyPolarisationSurvey-User Experience, Algorithmic Logic Searchhttps://www.nature.com/articles/s41586-023-06078-5#ref-CR3
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Schellingerhout et al. 2023
Accounting for Personalization in Personalization Algorithms: YouTube’s Treatment of Conspiracy Content
YouTubeThird-partyRabbit HoleAutomatedSockPuppetAlgorithmic LogicRecSyshttps://www.tandfonline.com/doi/full/10.1080/21670811.2023.2209153
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Semenova2023
The Tree of Complexity. Analyzing YouTube's Interconnected Components as a Case Study for Comprehensive Platform Audits and Risk Assessment
YouTubeThird-Party-Crowdsourced-Algorithmic LogicRecSyshttps://www.stiftung-nv.de/de/publication/the-tree-of-complexity
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Steen et al.2023
You Can (Not) Say What You Want: Using Algospeak to Contest and Evade Algorithmic Content Moderation on TikTok
TikTokThird-PartyAlgospeakSurvey-Content Moderation-https://journals.sagepub.com/doi/10.1177/20563051231194586
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Vekaria et al.2023
Before Blue Birds Became X-tinct: Understanding the Effect of Regime Change on Twitter’s Advertising and Compliance of Advertising Policies
TwitterThird-PartyAdvertisementAutomatedAPIAdvertisement-https://arxiv.org/abs/2309.12591
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Votta et al.2023Going Micro to Go Negative? Targeting Toxicity using Facebook and Instagram AdsFacebookThird-partyAdsAutomatedAPIUser Experience; Algorithmic LogicRecSyshttps://www.aup-online.com/content/journals/10.5117/CCR2023.1.001.VOTT
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Zieringer & Rieger2023
Algorithmic Recommendations’ Role for the Interrelatedness of Counter-Messages and Polluted Content on YouTube – A Network Analysis
YouTubeThird-PartyRadicalisationAutomatedAPIAlgorithmic LogicRecSyshttps://www.aup-online.com/content/journals/10.5117/CCR2023.1.005.ZIER
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Boeker & Urman2022An Empirical Investigation of Personalization Factors on TikTokTikTokThird-party-AutomatedSockPuppetAlgorithmic LogicRecSyshttps://dl.acm.org/doi/10.1145/3485447.3512102
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Bonifazi et al.2022
Extracting time patterns from the lifespans of TikTok challenges to characterize non-dangerous and dangerous ones
TikTokThird-PartyChallengesAutomatedScrapingContent Moderation; User Experience-https://link.springer.com/article/10.1007/s13278-022-00893-w
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Brown et al.2022
Echo Chambers, Rabbit Holes, and Algorithmic Bias: How YouTube Recommends Content to Real Users
YouTubeThird-partyEcho Chambers / Rabbit Hole / BiasCrowdsourced-Algorithmic LogicRecSyshttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=4114905
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Center for Countering Digital Hate
2022
Deadly by Design. TikTok pushes harmful content promoting eating disorders and self-harm into young users’ feeds
TikTokThird-PartySelf-harmAutomatedSockPuppetAlgorithmic LogicRecSyshttps://counterhate.com/research/deadly-by-design/
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Chen et al.2022
Subscriptions and external links help drive resentful users to alternative and extremist YouTube videos
YouTubeThird-partyRabbit HoleCrowdsourced; Survey-Algorithmic LogicRecSyshttps://arxiv.org/abs/2204.10921
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Ernala et al.2022
Mindsets Matter: How Beliefs About Facebook Moderate the Association Between Time Spent and Well-Being
FacebookFirst-PartyWell-BeingSurvey; Data-User Experience-https://dl.acm.org/doi/abs/10.1145/3491102.3517569
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Guinaudeau et al.2022Fifteen Seconds of Fame: TikTok and the Supply Side of Social VideoTikTokThird-party-AutomatedAPIAlgorithmic Logic; User ExperienceRecSyshttps://www.aup-online.com/content/journals/10.5117/CCR2022.2.004.GUIN
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Haroon et al.2022
YouTube, The Great Radicalizer? Auditing and Mitigating Ideological Biases in YouTube Recommendations
YouTubeThird-partyBias; Rabbit HoleAutomatedSockPuppetAlgorithmic LogicRecSyshttps://arxiv.org/abs/2203.10666
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Horten2022Algorithms Patrolling Content: Where’s the Harm?FacebookThird-partyShadowBanningAutomated; SurveyScrapingContent Moderation; Algorithmic LogicRecSyshttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=3792097
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Jürgens & Stark2022
Mapping Exposure Diversity: The Divergent Effects of Algorithmic Curation on News Consumption
Facebook; Twitter
Third-partyEchoChamberCrowdsourced-User Experience-https://academic.oup.com/joc/article/72/3/322/6549217?login=true
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Kim et al.2022A Shape of Geo-tagged Media Bias in COVID-19 Related TwitterTwitterThird-partyBiasAutomated-User Experience-https://dl.acm.org/doi/10.1145/3568562.3568644
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Matias et al.2022
Software-Supported Audits of Decision-Making Systems: Testing Google and Facebook’s Political Advertising Policies
Facebook; Google
Third-partyAdsAutomatedAPIContent Moderation-https://dl.acm.org/doi/10.1145/3512965
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Pailleux et al. 2022Are YouTube algorithms addicted to State-controlled media?YouTubeThird-partyDisinformationAutomatedAPI; SockPuppetAlgorithmic LogicRecSyshttps://crossover.social/are-youtube-algorithms-addicted-to-state-controlled-media/
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Papakyriakopoulos et al.2022
How Algorithms Shape the Distribution of Political Advertising: Case Studies of Facebook, Google, and TikTok
Facebook; Google; TikTok
Third-partyAdsAutomatedAPI; ScrapingAdvertisement; Algorithmic LogicAdshttps://dl.acm.org/doi/10.1145/3514094.3534166
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Romano & Faddoul2022
Mapping Ban and Shadow-Ban on TikTok: Expose hidden censorship with a cross-national research
TikTokThird-partyShadow BanningAutomatedSockPuppets; ScrapingContent Moderation; Algorithmic LogicRecSyshttps://wiki.digitalmethods.net/Dmi/WinterSchool2022TikTokShadowBan
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Srba et al.2022Auditing YouTube’s Recommendation Algorithm for Misinformation Filter BubblesYouTubeThird-partyDisinformationAutomatedSockPuppetAlgorithmic LogicSearch, RecSyshttps://arxiv.org/abs/2210.10085
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TrackingExposed2022Shadow-promotion: TikTok’s algorithmic recommendation of banned content in RussiaTikTokThird-partyShadow Banning / PromotionAutomatedSockPuppetAlgorithmic Logic; Content ModerationRecSyshttps://tracking.exposed/pdf/tiktok-russia-ShadowPromotion.pdf
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Turnbull et al.2022
Exploring Popularity Bias in Music Recommendation Models and Commercial Steaming Services
Spotify; Amazon Music; YouTube Music
Third-partyPopularity BiasAutomatedSockPuppetAlgorithmic LogicRecSyshttps://arxiv.org/abs/2208.09517
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Weiss et al.2022The Twitter FilesTwitterSecond-partyShadowBanningDocument-Content Moderation-https://www.thefp.com/p/the-story-behind-the-twitter-files
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Wojcik et al.2022
Birdwatch: Crowd Wisdom and Bridging Algorithms can Inform Understanding and Reduce the Spread of Misinformation
TwitterFirst-partyMisinformationSurvey; Architecture-User Interface; Algorithmic LogicRecSyshttps://arxiv.org/abs/2210.15723
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Zade et al.2022
Auditing Google’s Search Headlines as a Potential Gateway to Misleading Content: Evidence from the 2020 US Election
GoogleThird-PartyMisinformationAutomatedScrapingAlgorithmic LogicSearchhttps://www.tsjournal.org/index.php/jots/article/view/72/33
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Zeng & Kaye2022
From content moderation to visibility moderation: A case study of platform governance on TikTok
TikTokThird-partyShadowBanningSurvey-Content Moderation, Algorithmic LogicRecSyshttps://onlinelibrary.wiley.com/doi/full/10.1002/poi3.287
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Alfano et al.2021
Technologically scaffolded atypical cognition: the case of YouTube’s recommender system
YouTubeThird-partyRabbit HoleAutomatedAPIAlgorithmic LogicRecSyshttps://link.springer.com/article/10.1007/s11229-020-02724-x
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Ali et al.2021Ad Delivery Algorithms: The Hidden Arbiters of Political MessagingFacebookThird-partyAdsAutomated-Advertisement-https://dl.acm.org/doi/10.1145/3437963.3441801
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Asimovic et al.2021Testing the effects of Facebook usage in an ethnically polarized settingFacebookThird-PartyPolarizationSurvey-User Experience-https://www.pnas.org/doi/full/10.1073/pnas.2022819118
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Bandy & Diakopoulos2021
More Accounts, Fewer Links: How Algorithmic Curation Impacts Media Exposure in Twitter Timelines
TwitterThird-partyFilterBubbleAutomatedSockPuppet;APIAlgorithmic LogicRecSyshttps://dl.acm.org/doi/10.1145/3449152
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Bandy & Diakopoulos2021Curating quality? How Twitter’s timeline algorithm treats different types of newsTwitterThird-Party-AutomatedAPIAlgorithmic LogicRecSyshttps://journals.sagepub.com/doi/10.1177/20563051211041648
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Bartlett et al.2021
Analysing Privacy Policies and Terms of Use to understand algorithmic recommendations: the case studies of Tinder and Spotify
Tinder; SpotifyThird-partyPrivacy related risksDocument-Terms & Conditions; Algorithmic LogicRecSyshttps://www.tandfonline.com/doi/full/10.1080/03036758.2022.2064517
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Bartley et al.2021Auditing Algorithmic Bias on TwitterTwitterThird-partyBiasAutomatedSockPuppetAlgorithmic LogicRecSyshttps://dl.acm.org/doi/10.1145/3447535.3462491
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Bösch & Mozilla2021Broken Promises: TikTok and the German ElectionTikTokThird-partyDisinformation
Document; Automated
-
User Interface; Content Moderation; Terms & Conditions
-https://foundation.mozilla.org/en/campaigns/tiktok-german-election-2021/
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Brown et al.2021Twitter amplifies conservative politicians. Is it because users mock them?TwitterThird-partyBiasAutomated-Algorithmic LogicRecSyshttps://www.washingtonpost.com/outlook/2021/10/27/twitter-amplifies-conservative-politicians/
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Buntain et al.2021YouTube Recommendations and Effects on Sharing Across Online Social PlatformsYouTubeThird-partyExtremist ContentAutomatedAPIAlgorithmic LogicRecSyshttps://dl.acm.org/doi/10.1145/3449085
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Chen et al.2021Exposure to Alternative & Extremist Content on YouTubeYouTubeThird-partyRabbit HoleSurvey; Crowdsourced-Algorithmic Logic-https://www.adl.org/resources/reports/exposure-to-alternative-extremist-content-on-youtube
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Chen et al.2021Neutral bots probe political bias on social mediaTwitterThird-PartyBiasAutomatedSock PuppetAlgorithmic LogicRecSyshttps://www.nature.com/articles/s41467-021-25738-6
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Donkers & Ziegler 2021
The Dual Echo Chamber: Modeling Social Media Polarization for Interventional Recommending
TwitterThird-partyPolarizationAutomatedScrapingAlgorithmic LogicRecSyshttps://dl.acm.org/doi/10.1145/3460231.3474261
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Haugen2021Facebook PapersFacebookThird-party
Polarization; Hate Speech; Mental Health; Disinformation
Document-Algorithmic Logic; AdsRecSyshttps://facebookpapers.com/
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Heuer et al.2021Auditing the Biases Enacted by YouTube for Political Topics in GermanyYouTubeThird-partyBiasAutomatedSockPuppetAlgorithmic LogicRecSyshttps://arxiv.org/abs/2107.09922
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Hosseinmardi et al.2021Examining the consumption of radical content on YouTubeYouTubeThird-partyRabbit HoleCrowdsourced-Algorithmic Logic-https://www.pnas.org/doi/10.1073/pnas.2101967118
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Huszár et al.2021Algorithmic Amplification of Politics on TwitterTwitterFirst-partyBiasArchitecture-Algorithmic LogicRecSyshttps://www.pnas.org/doi/10.1073/pnas.2025334119
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Imana et al.2021Auditing for Discrimination in Algorithms Delivering Job Ads
Facebook; LinkedIn
Third-partyAdsAutomatedSockPuppetAlgorithmic Logic; Advertisement-https://dl.acm.org/doi/10.1145/3442381.3450077
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Jennings et al.2021Asymmetric adjustment: Partisanship and correcting misinformation on FacebookFacebookThird-PartyMisinformationSurvey-User Experience-https://journals.sagepub.com/doi/10.1177/14614448211021720
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Kalimeris et al.2021Preference Amplification in Recommender SystemsFacebookFirst-partyFilter BubbleArchitecture-Algorithmic LogicRecSyshttps://research.facebook.com/publications/preference-amplification-in-recommender-systems/
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Klug et al.2021
Trick and Please. A Mixed-Method Study On User Assumptions About the TikTok Algorithm
TikTokThird-party-Survey; Automated-Algorithmic LogicRecSyshttps://dl.acm.org/doi/10.1145/3447535.3462512
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Kübler et al.2021
The 2021 German Federal Election on Social Media: An Analysis of Systemic Electoral Risks Created by Twitter and Facebook Based on the Proposed EU Digital Services Act
Twitter, Facebook
Third-party
Electoral Risks; Illegal Content; Negative effects on electoral rights; Disinformation
AutomatedAPIContent Moderation; Terms & Conditions-https://www.sustainablecomputing.eu/wp-content/uploads/2021/10/DE_Elections_Report_Final_17.pdf
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Matamoros-Fernández et al.2021
What’s “Up Next”? Investigating Algorithmic Recommendations on YouTube Across Issues and Over Time
YouTubeThird-partyBiasAutomatedAPI / ScrapingAlgorithmic LogicRecSyshttps://www.cogitatiopress.com/mediaandcommunication/article/view/4184
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Meta2021Instagram Teen Annotated ResearchInstagramFirst-partyWell-BeingSurvey-User Experience-https://about.fb.com/news/2021/09/research-teen-well-being-and-instagram/
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Morales & Cointet2021
Auditing the Effect of Social Network Recommendations on Polarization in Geometrical Ideological Spaces
TwitterThird-partyPolarizationAutomated-Algorithmic Logic; User ExperienceRecSyshttps://dl.acm.org/doi/fullHtml/10.1145/3460231.3478851
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Mozilla2021These Are “Not” Political AdsTikTokThird-partyAds
Automated; Document
APIAdvertisement; Terms & Conditions-https://foundation.mozilla.org/en/campaigns/tiktok-political-ads/
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Mozilla2021
YouTube Regrets: A crowdsourced investigation into YouTube’s recommendation algorithm
YouTubeThird-partyHarmsCrowdsourced-
Algorithmic Logic; User Experience; Terms & Conditions
RecSyshttps://foundation.mozilla.org/en/youtube/findings/
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Murthy2021Evaluating Platform Accountability: Terrorist Content on YouTubeYouTubeThird-partyTerrorist contentAutomatedAPIContent Moderation; Algorithmic Logic-https://journals.sagepub.com/doi/full/10.1177/0002764221989774
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Osmundsen et al.2021
Partisan Polarization Is the Primary Psychological Motivation behind Political Fake News Sharing on Twitter
TwitterThird-PartyMisinformation--User Experience-
https://www.cambridge.org/core/journals/american-political-science-review/article/abs/partisan-polarization-is-the-primary-psychological-motivation-behind-political-fake-news-sharing-on-twitter/3F7D2098CD87AE5501F7AD4A7FA83602
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Papadamou et al.2021"How over is it?" Understanding the Incel Community on YouTubeYouTubeThird-partyRabbit HoleAutomatedAPIAlgorithmic LogicRecSyshttps://arxiv.org/abs/2001.08293
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Papadamou et al.2021
Disturbed YouTube for Kids: Characterizing and Detecting Inappropriate Videos Targeting Young Children
YouTubeThird-partyInappropriate ContentAutomatedAPIContent Moderation; Algorithmic LogicRecSyshttps://arxiv.org/abs/1901.07046
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Tomlein et al.2021
An Audit of Misinformation Filter Bubbles on YouTube: Bubble Bursting and Recent Behavior Changes
YouTubeThird-partyDisinformationAutomatedSockPuppetAlgorithmic LogicSearch, RecSyshttps://arxiv.org/abs/2203.13769
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TrackingExposed2021FilterTube: Investigating echo chambers, filter bubbles and polarization on YouTubeYouTubeThird-partyFilterBubble; PolarizationAutomatedSockPuppetAlgorithmic LogicRecSyshttps://youtube.tracking.exposed/filtertube/
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Urman et al.2021Auditing Source Diversity Bias in Video Search Results Using Virtual AgentsGoogleThird-partyBiasAutomatedSockPuppetAlgorithmic LogicSearchhttps://arxiv.org/abs/2106.02715
100
Wall Street Journal2021Inside TikTok’s Algorithm: A WSJ Video InvestigationTikTokThird-partyMental Health; Rabbit HoleAutomatedSockPuppetAlgorithmic LogicRecSyshttps://www.wsj.com/articles/tiktok-algorithm-video-investigation-11626877477