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.
CITATION STYLE
Song, Y., & Zhang, Y. (2017). 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. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10540 LNCS, pp. 230–241). Springer Verlag. https://doi.org/10.1007/978-3-319-67256-4_18
Mendeley helps you to discover research relevant for your work.