What Can Software Tell Us About Media Coverage and Public Opinion? An Analysis of Political News Posts and Audience Comments on Facebook by Computerised Method

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10540)


In this exploratory study, we applied an automated linguistic analysis method (TextMind) to a social movement context by comparing a sample set of online news posts (N1 = 13,434) with audience comments to the posts (N2 = 1,998,095) on Facebook. The findings of this study revealed that there were, in fact, linguistic differences between the news posts by news media outlets and their corresponding audience comments. TextMind is able to detect such linguistic differences and their changes over time. Comparative findings suggest: (1) The linguistic choices of news reporting are affected by news media’s (or journalists’) political, ideological, and market orientations. (2) The language used by traditional newspapers is not necessarily more conservative or moderate in emotion than their online competitors. (3) Linguistic choices in news posts would change over periods of time. However, (4) the language patterns of news posts did not directly affect linguistic choices of audiences in opinion expression, which remained relatively consistent.


Media coverage Public opinion Automated linguistic analysis TextMind Facebook 



We gratefully acknowledge the Research Grants Committee of Hong Kong for providing a generous research grant (HKBU 12632816) for a larger project on which this article is based.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of JournalismHong Kong Baptist UniversityKowloon TongHong Kong S.A.R.

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