The Impact of Featuring Comments in Online Discussions

• URL: http://arxiv.org/abs/2412.02369v1
• Date: Tue, 03 Dec 2024 10:53:22 GMT
• Title: The Impact of Featuring Comments in Online Discussions
• Authors: Cedric Waterschoot, Ernst van den Hemel, Antal van den Bosch,
• Abstract summary: We compare online discussions of news articles in which certain comments are featured, versus discussions in which no comments are featured. We measure the impact of featuring comments on the discussion, by estimating and comparing the quality of discussions from the perspective of the user base and the platform itself.
• Score: 1.4255659581428335
• License:
• Abstract: A widespread moderation strategy by online news platforms is to feature what the platform deems high quality comments, usually called editor picks or featured comments. In this paper, we compare online discussions of news articles in which certain comments are featured, versus discussions in which no comments are featured. We measure the impact of featuring comments on the discussion, by estimating and comparing the quality of discussions from the perspective of the user base and the platform itself. Our analysis shows that the impact on discussion quality is limited. However, we do observe an increase in discussion activity after the first comments are featured by moderators, suggesting that the moderation strategy might be used to increase user engagement and to postpone the natural decline in user activity over time.

Related papers

• ArguMentor: Augmenting User Experiences with Counter-Perspectives [4.84187718353576]
  ArguMentor is a human-AI collaboration system that highlights claims in opinion pieces. It identifies counter-arguments for them using a LLM and generates a context-based summary of based on current events. It further enhances user understanding through additional features like a Q&A bot and DebateMe.
  arXiv  Detail & Related papers  (2024-06-04T21:43:56Z)
• Rethinking the Evaluation of Dialogue Systems: Effects of User Feedback on Crowdworkers and LLMs [57.16442740983528]
  In ad-hoc retrieval, evaluation relies heavily on user actions, including implicit feedback. The role of user feedback in annotators' assessment of turns in a conversational perception has been little studied. We focus on how the evaluation of task-oriented dialogue systems ( TDSs) is affected by considering user feedback, explicit or implicit, as provided through the follow-up utterance of a turn being evaluated.
  arXiv  Detail & Related papers  (2024-04-19T16:45:50Z)
• Context Does Matter: Implications for Crowdsourced Evaluation Labels in Task-Oriented Dialogue Systems [57.16442740983528]
  Crowdsourced labels play a crucial role in evaluating task-oriented dialogue systems. Previous studies suggest using only a portion of the dialogue context in the annotation process. This study investigates the influence of dialogue context on annotation quality.
  arXiv  Detail & Related papers  (2024-04-15T17:56:39Z)
• ViCo: Engaging Video Comment Generation with Human Preference Rewards [68.50351391812723]
  We propose ViCo with three novel designs to tackle the challenges for generating engaging Video Comments. To quantify the engagement of comments, we utilize the number of "likes" each comment receives as a proxy of human preference. To automatically evaluate the engagement of comments, we train a reward model to align its judgment to the above proxy.
  arXiv  Detail & Related papers  (2023-08-22T04:01:01Z)
• Fostering User Engagement in the Critical Reflection of Arguments [3.26297440422721]
  We propose a system that engages in a deliberative dialogue with a human. We enable the system to intervene if the user is too focused on their pre-existing opinion. We report on a user study with 58 participants to test our model and the effect of the intervention mechanism.
  arXiv  Detail & Related papers  (2023-08-17T15:48:23Z)
• Analyzing Norm Violations in Live-Stream Chat [49.120561596550395]
  We study the first NLP study dedicated to detecting norm violations in conversations on live-streaming platforms. We define norm violation categories in live-stream chats and annotate 4,583 moderated comments from Twitch. Our results show that appropriate contextual information can boost moderation performance by 35%.
  arXiv  Detail & Related papers  (2023-05-18T05:58:27Z)
• Thread With Caution: Proactively Helping Users Assess and Deescalate Tension in Their Online Discussions [13.455968033357065]
  Incivility remains a major challenge for online discussion platforms. Traditionally, platforms have relied on moderators to -- with or without algorithmic assistance -- take corrective actions such as removing comments or banning users. We propose a complementary paradigm that directly empowers users by proactively enhancing their awareness about existing tension in the conversation they are engaging in.
  arXiv  Detail & Related papers  (2022-12-02T19:00:03Z)
• Persua: A Visual Interactive System to Enhance the Persuasiveness of Arguments in Online Discussion [52.49981085431061]
  Enhancing people's ability to write persuasive arguments could contribute to the effectiveness and civility in online communication. We derived four design goals for a tool that helps users improve the persuasiveness of arguments in online discussions. Persua is an interactive visual system that provides example-based guidance on persuasive strategies to enhance the persuasiveness of arguments.
  arXiv  Detail & Related papers  (2022-04-16T08:07:53Z)
• Explainable Patterns for Distinction and Prediction of Moral Judgement on Reddit [8.98624781242271]
  The forum r/AmITheAsshole in Reddit hosts discussion on moral issues based on concrete narratives presented by users. We build a new dataset of comments and also investigate the classification of the posts in the forum.
  arXiv  Detail & Related papers  (2022-01-26T19:39:52Z)
• News consumption and social media regulations policy [70.31753171707005]
  We analyze two social media that enforced opposite moderation methods, Twitter and Gab, to assess the interplay between news consumption and content regulation. Our results show that the presence of moderation pursued by Twitter produces a significant reduction of questionable content. The lack of clear regulation on Gab results in the tendency of the user to engage with both types of content, showing a slight preference for the questionable ones which may account for a dissing/endorsement behavior.
  arXiv  Detail & Related papers  (2021-06-07T19:26:32Z)
• Linking the Dynamics of User Stance to the Structure of Online Discussions [6.853826783413853]
  We investigate whether users' stance concerning contentious subjects is influenced by the online discussions they are exposed to. We set up a series of predictive exercises based on machine learning models. We find that the most informative features relate to the stance composition of the discussion in which users prefer to engage.
  arXiv  Detail & Related papers  (2021-01-25T02:08:54Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.