Issue-focused documentaries versus other films: Rating and type prediction based on user-authored reviews

Ming Jiang, Jana Diesner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

User-authored reviews offer a window into micro-level engagement with issue-focused documentary films, which is a critical yet insufficiently understood topic in media impact assessment. Based on our data, features, and supervised learning method, we find that ratings of non-documentary (feature film) reviews can be predicted with higher accuracy (73.67%, F1 score) than ratings of documentary reviews (68.05%). We also constructed a classifier that separates reviews of documentaries from reviews of feature films with an accuracy of 71.32%. However, as our goal with this paper is not to improve the accuracy of predicting the rating and type or genre of film reviews, but to advance our understanding of the perception of documentaries in comparison to feature films, we also identified commonalities and differences between these two types of films as well as between low versus high ratings. We find that in contrast to reviews of feature films, comments on documentaries are shorter but composed of longer sentences, are less emotional, contain less positive and more negative terms, are lexically more concise, and are more focused on verbs than on nouns and adjectives. Compared to low-rated reviews, comments with a high rating are shorter, are more emotional and contain more positive than negative sentiment, and have less question marks and more exclamation points. Overall, this work contributes to advancing our understanding of the impact of different types of information products on individual information consumers.

Original languageEnglish (US)
Title of host publicationHT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media
PublisherAssociation for Computing Machinery, Inc
Pages225-230
Number of pages6
ISBN (Electronic)9781450342476
DOIs
StatePublished - Jul 10 2016
Event27th ACM Conference on Hypertext and Social Media, HT 2016 - Halifax, Canada
Duration: Jul 10 2016Jul 13 2016

Publication series

NameHT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media

Other

Other27th ACM Conference on Hypertext and Social Media, HT 2016
CountryCanada
CityHalifax
Period7/10/167/13/16

Keywords

  • Documentary films
  • Rating prediction
  • Social impact
  • Type prediction

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software
  • Artificial Intelligence

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  • Cite this

    Jiang, M., & Diesner, J. (2016). Issue-focused documentaries versus other films: Rating and type prediction based on user-authored reviews. In HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media (pp. 225-230). (HT 2016 - Proceedings of the 27th ACM Conference on Hypertext and Social Media). Association for Computing Machinery, Inc. https://doi.org/10.1145/2914586.2914638