Metadata correction for 2024.findings-acl.944

[mjpost]

{
  "anthology_id": "2024.findings-acl.944",
  "title": "A Survey on Predicting the Factuality and the Bias of News Media",
  "authors": [
    {
      "first": "Preslav",
      "last": "Nakov",
      "id": "preslav-nakov",
      "affiliation": ""
    },
    {
      "first": "Jisun",
      "last": "An",
      "id": "jisun-an",
      "affiliation": ""
    },
    {
      "first": "Haewoon",
      "last": "Kwak",
      "id": "haewoon-kwak",
      "affiliation": ""
    },
    {
      "first": "Muhammad Arslan",
      "last": "Manzoor",
      "id": "muhammad-arslan-manzoor",
      "affiliation": ""
    },
    {
      "first": "Zain Muhammad",
      "last": "Mujahid",
      "id": "zain-muhammad-mujahid",
      "affiliation": ""
    },
    {
      "first": "Husrev",
      "last": "Sencar",
      "id": "husrev-sencar",
      "affiliation": ""
    }
  ],
  "abstract": "The present level of proliferation of fake, biased, and propagandistic content online has made it impossible to fact-check every single suspicious claim or article, either manually or automatically. An increasing number of scholars are focusing on a coarser granularity, aiming to profile entire news outlets, which allows fast identification of potential “fake news” by checking the reliability of their source. Source factuality is also an important element of systems for automatic fact-checking and “fake news” detection, as they need to assess the reliability of the evidence they retrieve online. Political bias detection, which in the Western political landscape is about predicting left-center-right bias, is an equally important topic, which has experienced a similar shift toward profiling entire news outlets. Moreover, there is a clear connection between the two, as highly biased media are less likely to be factual; yet, the two problems have been addressed separately. In this survey, we review the state of the art on media profiling for factuality and bias, arguing for the need to model them jointly. We also shed light on some of the major challenges for modeling bias and factuality jointly. We further discuss interesting recent advances in using different information sources and modalities, which go beyond the text of the articles the target news outlet has published. Finally, we discuss current challenges and outline future research directions."
}

[github-actions]

Found ACL Anthology entry:

📄 Paper: https://aclanthology.org/2024.findings-acl.944

[github-actions]

❌ LLM Validation Failed

Details:

• The proposed title 'A Survey on Predicting the Factuality and the Bias of News Media' does not match the title found in the PDF, which is 'A Survey on Predicting the Factuality and Bias of News Media'. The word 'the' before 'Bias' is missing in the original title.
• The proposed list of authors includes 'Preslav Nakov, Jisun An, Haewoon Kwak, Muhammad Arslan Manzoor, Zain Muhammad Mujahid, Husrev Sencar', which matches the authors listed in the PDF in both order and completeness.

[mjpost]

Perhaps of interest to @nschneid @mbollmann. Needs some work.

[zainmujahid]

    {
      "first": "Zain",
      "last": "Muhammad Mujahid",
      "id": "zain-mujahid",
      "affiliation": ""
    },

@mjpost Also, please note my id is zain-muhammad-mujahid, and not the one in your comment above.
Link: https://aclanthology.org/people/z/zain-muhammad-mujahid/

[mjpost]

Thanks, fixed. When this PR is merged, all your papers will show up under that ID.

(Sorry if you're getting many notices; you were randomly selected as a test case for a new feature :))

[zainmujahid]

@mjpost Thank you.

And no problem at all. I am happy to contribute.