12,637 papers · updated 10 Oct 2026livingmeta.ai
← Browse all papers
Research theme

Citation Integrity

The Citation Integrity theme comprises 248 papers in this corpus published between 1963 and 2026. Work here is dominated by Empirical Study, Benchmarking, Content Analysis. 5 open research gaps have been surfaced in this area.

Methodology profile

  • Empirical Study65 (26%)
  • Benchmarking27 (11%)
  • Content Analysis22 (9%)
  • Literature Review22 (9%)
  • Conceptual18 (7%)
  • Position Paper18 (7%)

Research domains

  • Research Integrity185 (75%)
  • Scholarly Infrastructure30 (12%)
  • Knowledge Synthesis10 (4%)
  • Peer Review7 (3%)
  • Academic Writing6 (2%)
  • Literature Discovery3 (1%)

Frequent sub-topics

technical barriers to copyright assessment in generative AI · 1Data rights and AI training data acquisition legality · 1contract law and copyright implications for AI training data · 1data scraping for AI training and copyright ethics · 1LLM-based plagiarism detection · 1citation formats in generative AI output · 1AI-generated academic citations accuracy · 1AI disclosure trends in corporate filings · 1

Open research gaps

  • Differentiation of retraction reasons (methodological errors, data fabrication, ethical violations, plagiarism) to determine if specific categories are more readily detectable through critical online
  • Analysis of thematic content of articles and its effects on frequency and tone of Twitter engagement
  • Incorporation of engagement metrics (likes, retweets, replies) and user contextual data (bot vs. journalist vs. academic accounts)
  • Extension of framework to emerging platforms such as Bluesky and Mastodon, given migration of researchers from Twitter
  • Investigation of the social amplification pathway and mechanisms by which critical tweets influence editorial decision-making

Representative papers

← Browse all papersPriority research agenda →