English

AudienceView: AI-Assisted Interpretation of Audience Feedback in Journalism

Human-Computer Interaction 2024-11-15 v1 Computation and Language

Abstract

Understanding and making use of audience feedback is important but difficult for journalists, who now face an impractically large volume of audience comments online. We introduce AudienceView, an online tool to help journalists categorize and interpret this feedback by leveraging large language models (LLMs). AudienceView identifies themes and topics, connects them back to specific comments, provides ways to visualize the sentiment and distribution of the comments, and helps users develop ideas for subsequent reporting projects. We consider how such tools can be useful in a journalist's workflow, and emphasize the importance of contextual awareness and human judgment.

Keywords

Cite

@article{arxiv.2407.12613,
  title  = {AudienceView: AI-Assisted Interpretation of Audience Feedback in Journalism},
  author = {William Brannon and Doug Beeferman and Hang Jiang and Andrew Heyward and Deb Roy},
  journal= {arXiv preprint arXiv:2407.12613},
  year   = {2024}
}

Comments

Accepted at CSCW Demo 2024. 5 pages, 2 figures