Mapping the public agenda with topic modeling: The case of the Russian livejournal

This article describes agendas as “packages” of topics of varying salience, set by the Russian Internet users on Russia's leading blog platform LiveJournal. The research involved modeling LiveJournal's topic structure, viewed as an important component of what is termed here self‐generated public opinion. Topic modeling was performed automatically with the LDA algorithm, and complemented with hand labeling of topics. Data were collected by software created by the authors to generate a relational database storing all posts by the top 2,000 LiveJournal users from three one‐month periods: two during the Russian parliamentary and presidential elections 2011–2012, and one control period. We find that LiveJournal top users share their attention evenly between “social/political” and “private/recreational” issues, the proportion being very stable. However, the substitution of diverse public affairs issues by the topics related to national street protests in the politicized periods compared to the control period was found both automatically and manually. The group of topics centered around social issues demonstrates the biggest volatility in terms of its composition and may serve as the foundation for monitoring self‐generated public opinion by further application of sentiment/opinion mining methods to these topics .