This paper presents the methodology and results of a project for the large-scale analysis of public messages in political discourse on Facebook, the dominant social media site in Hungary. We propose several novel social psychologymotivated dimensions for natural language processing-based text analysis that go beyond the standard sentiment-based analysis approaches. Communion describes the moral and emotional aspects of an individual's relations to others, while agency describes individuals in terms of the efficiency of their goalorientated behavior. We treat these by custom lexicons that identify positive and negative cues in text. We measure the level of optimism in messages by examining the ratio of events talked about in the past, present and future by looking at verb tenses and temporal expressions. For assessing the level of individualism, we build on research that correlates it to pronoun dropping. We also present results that demonstrate the viability of our measures on 1.9 million downloaded public Facebook comments by examining correlation to party preferences in public opinion poll data.