pith. machine review for the scientific record. sign in

arxiv: 1705.02673 · v1 · submitted 2017-05-07 · 💻 cs.SI

Recognition: unknown

Identifying the social signals that drive online discussions: A case study of Reddit communities

Authors on Pith no claims yet
classification 💻 cs.SI
keywords contentonlineanalysisdiscussionsredditsocialwhatattention
0
0 comments X
read the original abstract

Increasingly people form opinions based on information they consume on online social media. As a result, it is crucial to understand what type of content attracts people's attention on social media and drive discussions. In this paper we focus on online discussions. Can we predict which comments and what content gets the highest attention in an online discussion? How does this content differ from community to community? To accomplish this, we undertake a unique study of Reddit involving a large sample comments from 11 popular subreddits with different properties. We introduce a large number of sentiment, relevance, content analysis features including some novel features customized to reddit. Through a comparative analysis of the chosen subreddits, we show that our models are correctly able to retrieve top replies under a post with great precision. In addition, we explain our findings with a detailed analysis of what distinguishes high scoring posts in different communities that differ along the dimensions of the specificity of topic and style, audience and level of moderation.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. What Do AI Agents Talk About? Discourse and Architectural Constraints in the First AI-Only Social Network

    cs.CL 2026-03 unverdicted novelty 7.0

    Discourse among AI agents on Moltbook is largely determined by architectural constraints like context windows and identity files, appearing as social learning but actually short-horizon contextual conditioning.