Characterizing the Language of Online Communities and its Relation to Community Reception

This work investigates style and topic aspects of language in online communities: looking at both utility as an identifier of the community and correlation with community reception of content. Style is characterized using a hybrid word and part-of-speech tag n-gram language model, while topic is represented using Latent Dirichlet Allocation. Experiments with several Reddit forums show that style is a better indicator of community identity than topic, even for communities organized around specific topics. Further, there is a positive correlation between the community reception to a contribution and the style similarity to that community, but not so for topic similarity.

• Publication year

  2016

• Venue

  Conference on Empirical Methods in Natural Language Processing

• Publication date

  2016-09-15

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.18653/v1/D16-1108arXiv 1609.04779
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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