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Auditing Algorithmic Bias on Twitter

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/asi.24121openalex-snapshot
Quantifying Biases in Online Information Exposure
inferredcites →https://doi.org/10.1007/s11257-015-9165-3openalex-snapshot
What recommenders recommend: an analysis of recommendation biases and possible countermeasures
inferredcites →https://doi.org/10.1038/srep04343openalex-snapshot
The Simple Rules of Social Contagion
inferredcites →https://doi.org/10.1073/pnas.0605525103openalex-snapshot
Topical interests and the mitigation of search engine bias
inferredcites →https://doi.org/10.1080/15213269.2015.1006333openalex-snapshot
Effects of Popularity-Based News Recommendations (“Most-Viewed”) on Users' Exposure to Online News
inferredcites →https://doi.org/10.1093/poq/nfw006openalex-snapshot
Filter Bubbles, Echo Chambers, and Online News Consumption
inferredcites →https://doi.org/10.1098/rsif.2014.0378openalex-snapshot
The Matthew effect in empirical data
inferredcites →https://doi.org/10.1109/asonam.2018.8508659openalex-snapshot
Biases in the Facebook News Feed: A Case Study on the Italian Elections
inferredcites →https://doi.org/10.1109/bigdata47090.2019.9005951openalex-snapshot
Quantifying the Effects of Recommendation Systems
inferredcites →https://doi.org/10.1126/science.1121066openalex-snapshot
Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market
inferredcites →https://doi.org/10.1126/science.aaa1160openalex-snapshot
Exposure to ideologically diverse news and opinion on Facebook
inferredcites →https://doi.org/10.1145/1454008.1454012openalex-snapshot
The long tail of recommender systems and how to leverage it
inferredcites →https://doi.org/10.1145/1722149.1722154openalex-snapshot
From hits to niches?
inferredcites →https://doi.org/10.1145/2872427.2883040openalex-snapshot
The Effect of Recommendations on Network Structure
inferredcites →https://doi.org/10.1145/2998181.2998321openalex-snapshot
Quantifying Search Bias
inferredcites →https://doi.org/10.1145/3038912.3052680openalex-snapshot
Taming the Unpredictability of Cultural Markets with Social Influence
inferredcites →https://doi.org/10.1145/3209581openalex-snapshot
Bias on the web
inferredcites →https://doi.org/10.1145/3240323.3240370openalex-snapshot
How algorithmic confounding in recommendation systems increases homogeneity and decreases utility
inferredcites →https://doi.org/10.1145/3274417openalex-snapshot
Auditing Partisan Audience Bias within Google Search
inferredcites →https://doi.org/10.1177/0093650212466406openalex-snapshot
Selective Exposure in the Age of Social Media
inferredcites →https://doi.org/10.1177/0093650213497979openalex-snapshot
Automating the News
inferredcites →https://doi.org/10.1371/journal.pone.0098914openalex-snapshot
Leveraging Position Bias to Improve Peer Recommendation
inferredcites →https://doi.org/10.1371/journal.pone.0121934openalex-snapshot
The Benefits of Social Influence in Optimized Cultural Markets
inferredcites →https://doi.org/10.1609/icwsm.v14i1.7277openalex-snapshot
Auditing News Curation Systems: A Case Study Examining Algorithmic and Editorial Logic in Apple News
inferredcites →https://doi.org/10.1609/icwsm.v14i1.7337openalex-snapshot
Variation across Scales: Measurement Fidelity under Twitter Data Sampling
inferredcites →https://doi.org/10.1609/icwsm.v8i1.14549openalex-snapshot
Quantifying Information Overload in Social Media and Its Impact on Social Contagions
inferredcites →https://doi.org/10.2196/26692openalex-snapshot
Political Partisanship and Antiscience Attitudes in Online Discussions About COVID-19: Twitter Content Analysis
inferredcites →https://doi.org/10.48550/arxiv.1704.01347openalex-snapshot
Quantifying Search Bias: Investigating Sources of Bias for Political Searches in Social Media
inferredcites →https://doi.org/10.48550/arxiv.2011.08498openalex-snapshot
Political Partisanship and Anti-Science Attitudes in Online Discussions about Covid-19

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Auditing Political Exposure Bias: Algorithmic Amplification on Twitter/X Approaching the 2024 U.S. Presidential Election
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Patterns, Models, and Challenges in Online Social Media: A Survey
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What's in your PIE ? Understanding the contents of personalized information environments with PIEGraph
inferred← citeshttps://doi.org/10.1002/asi.70114openalex-snapshot
Conceptualizing algorithmic inequality and future agenda. An annual review of information science and technology (ARIST) paper
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Smart City
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Smart City: A Universal Approach in Particular Contexts
inferred← citeshttps://doi.org/10.1007/978-3-030-93413-2_15openalex-snapshot
Exploring Bias and Information Bubbles in YouTube’s Video Recommendation Networks
inferred← citeshttps://doi.org/10.1007/978-3-031-53503-1_11openalex-snapshot
Algorithmic Amplification of Politics and Engagement Maximization on Social Media
inferred← citeshttps://doi.org/10.1007/978-3-031-75204-9_13openalex-snapshot
Measuring the Echo-Chamber Phenomenon Through Exposure Bias
inferred← citeshttps://doi.org/10.1007/978-3-031-78538-2_3openalex-snapshot
Impacts of Personalization on Social Network Exposure
inferred← citeshttps://doi.org/10.1007/978-3-031-82431-9_36openalex-snapshot
Algorithmic Influence on Conflict and Cooperation in Digital Communities
inferred← citeshttps://doi.org/10.1007/978-3-032-05099-1_1openalex-snapshot
Cultural and Emotional Grounds for Image Choice in Twitter: The Case of #omicron Variant
inferred← citeshttps://doi.org/10.1007/978-3-658-46851-4_33-1openalex-snapshot
Algorithmisierte Medienumgebungen
inferred← citeshttps://doi.org/10.1007/s11109-025-10115-6openalex-snapshot
U.S. Partisan Media Criticize the Out-Party More than They Praise the In-Party
inferred← citeshttps://doi.org/10.1007/s41109-024-00668-6openalex-snapshot
Auditing the audits: evaluating methodologies for social media recommender system audits
inferred← citeshttps://doi.org/10.1007/s44206-023-00074-yopenalex-snapshot
Auditing of AI: Legal, Ethical and Technical Approaches
inferred← citeshttps://doi.org/10.1016/j.caeai.2024.100303openalex-snapshot
AI-based prediction of academic success: Support for many, disadvantage for some?
inferred← citeshttps://doi.org/10.1016/j.ssmqr.2026.100730openalex-snapshot
Parasocial paternalism and embodied advice: How cosmetic medicine interventions are marketed on TikTok
inferred← citeshttps://doi.org/10.1016/j.tele.2023.101999openalex-snapshot
Bubbles bursting: Investigating and measuring the personalisation of social media searches
inferred← citeshttps://doi.org/10.1038/s41598-022-19837-7openalex-snapshot
Partisan asymmetries in exposure to misinformation
inferred← citeshttps://doi.org/10.1038/s41598-022-21861-6openalex-snapshot
A comparative framework to analyze convergence on Twitter electoral conversations
inferred← citeshttps://doi.org/10.1038/s41598-023-43980-4openalex-snapshot
Crowdsourced audit of Twitter’s recommender systems
inferred← citeshttps://doi.org/10.1038/s41598-025-02261-yopenalex-snapshot
Digital inequality and neighborhood divides in online social networks in Chicago
inferred← citeshttps://doi.org/10.1038/s43588-026-01038-1openalex-snapshot
Algorithmic systems, human agency and the future of platform research
inferred← citeshttps://doi.org/10.1080/19312458.2023.2181319openalex-snapshot
Digital Trace Data Collection for Social Media Effects Research: APIs, Data Donation, and (Screen) Tracking
inferred← citeshttps://doi.org/10.1093/oxfordhb/9780198869252.013.41openalex-snapshot
Digital Culture
inferred← citeshttps://doi.org/10.1108/jices-03-2023-0029openalex-snapshot
Social and digital media monitoring for nonviolence: a distributed cognition perspective of the precariousness of peace work
inferred← citeshttps://doi.org/10.1109/access.2023.3262026openalex-snapshot
Autoencoder-Based Recommender System Exploiting Natural Noise Removal
inferred← citeshttps://doi.org/10.1126/sciadv.abn9418openalex-snapshot
Most users do not follow political elites on Twitter; those who do show overwhelming preferences for ideological congruity
inferred← citeshttps://doi.org/10.1140/epjds/s13688-026-00629-2openalex-snapshot
Dynamics of algorithmic content amplification on TikTok
inferred← citeshttps://doi.org/10.1145/3501247.3531546openalex-snapshot
The Effect of Hiding Dislikes on the Use of YouTube's Like and Dislike Features
inferred← citeshttps://doi.org/10.1145/3532106.3533449openalex-snapshot
Slanted Speculations:
inferred← citeshttps://doi.org/10.1145/3546915openalex-snapshot
Using Agent-Based Modelling to Evaluate the Impact of Algorithmic Curation on Social Media
inferred← citeshttps://doi.org/10.1145/3579610openalex-snapshot
Having your Privacy Cake and Eating it Too: Platform-supported Auditing of Social Media Algorithms for Public Interest
inferred← citeshttps://doi.org/10.1145/3610195openalex-snapshot
Marginalization and the Construction of Mental Illness Narratives Online: Foregrounding Institutions in Technology-Mediated Care
inferred← citeshttps://doi.org/10.1145/3613904.3642120openalex-snapshot
Mapping the Design Space of Teachable Social Media Feed Experiences
inferred← citeshttps://doi.org/10.1145/3630106.3658970openalex-snapshot
Law and the Emerging Political Economy of Algorithmic Audits
inferred← citeshttps://doi.org/10.1145/3715275.3732026openalex-snapshot
WEIRD Audits? Research Trends, Linguistic and Geographical Disparities in the Algorithm Audits of Online Platforms - A Systematic Literature Review
inferred← citeshttps://doi.org/10.1145/3715275.3732159openalex-snapshot
Auditing Political Exposure Bias: Algorithmic Amplification on Twitter/X During the 2024 U.S. Presidential Election
inferred← citeshttps://doi.org/10.1145/3717867.3717882openalex-snapshot
Social Biases in Knowledge Representations of Wikidata separates Global North from Global South
inferred← citeshttps://doi.org/10.1145/3805689.3812207openalex-snapshot
Exposure to news and political content on TikTok: A Case Study Around the 2024 US Election
inferred← citeshttps://doi.org/10.1177/14614448251339755openalex-snapshot
TikTok’s political landscape: Examining echo chambers and political expression dynamics
inferred← citeshttps://doi.org/10.1177/1532673x231184434openalex-snapshot
Building Support Through the Personalization of Twitter Messages in a Permanent Campaign
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Exploiting Social Capital for Recommendation in Social Networks
inferred← citeshttps://doi.org/10.1609/icwsm.v17i1.22187openalex-snapshot
Effects of Algorithmic Trend Promotion: Evidence from Coordinated Campaigns in Twitter’s Trending Topics
inferred← citeshttps://doi.org/10.2139/ssrn.4871612openalex-snapshot
Comparing the Usage of Russian-and Ukrainian-Derived Search Terms to Evaluate the Impact of Misinformation, Disinformation, and Propaganda in the US
inferred← citeshttps://doi.org/10.2196/36239openalex-snapshot
#BingeDrinking—Using Social Media to Understand College Binge Drinking: Qualitative Study
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GRAPH-BASED ANALYSIS OF INFORMATION FLOWS IN TELEGRAM FOR CYBERSECURITY THREAT DETECTION
inferred← citeshttps://doi.org/10.31219/osf.io/xvqz7openalex-snapshot
Law and the Emerging Political Economy of Algorithmic Audits
inferred← citeshttps://doi.org/10.4324/9781003472148-2openalex-snapshot
Making a Case for a Social Processes Approach to Online Hate
inferred← citeshttps://doi.org/10.5209/cgap.97604openalex-snapshot
Hacia una gobernanza algorítmica transparente: auditoría de sesgo. Estudio de caso.
inferred← citeshttps://doi.org/10.5210/fm.v27i12.12872openalex-snapshot
Twitter spam and false accounts prevalence, detection, and characterization: A survey
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It’s true, Australia won’t ban ‘sock puppet’ accounts on social media. Here’s why
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