Computational Discourse Resources

A list of useful and/or potentially useful sources for computationally analyzing conversations – a necessary step in the calculation of belief maps:

  • Computational Discourse Analysis
  • Towards computational discourse analysis: A methodology for mining Twitter backchanneling conversations
    • In this paper we present a methodology to analyze and visualize streams of Social Media messages and apply it to a case in which Twitter is used as a backchannel, i.e. as a communication medium through which participants follow an event in the real world as it unfolds. Unlike other methods based on social networks or theories of information diffusion, we do not assume proximity or a pre-existing social structure to model content generation and diffusion by distributed users; instead we refer to concepts and theories from discourse psychology and conversational analysis to track online interaction and discover how people collectively make sense of novel events through micro-blogging. In particular, the proposed methodology extracts concept maps from twitter streams and uses a mix of sentiment and topological metrics computed over the extracted concept maps to build visual devices and display the conversational flow represented as a trajectory through time of automatically extracted topics. We evaluated the proposed method through data collected from the analysis of Twitter users’ reactions to the March 2015 Apple Keynote during which the company announced the official launch of several new products.
  • MIT course by Regina Barzilay: Computational Models of Discourse (Slide deck) (syllabus with readings)
  • 5agado has a bunch of nice articles on Medium, linked to code. In particular, there’s Conversation Analyzer – An Introduction, with associated code.
  • High frequency word entrainment in spoken dialogue
    • Cognitive theories of dialogue hold that entrainment, the automatic alignment between dialogue partners at many levels of linguistic representation, is key to facilitating both production and comprehension in dialogue. In this paper we examine novel types of entrainment in two corpora—Switchboard and the Columbia Games corpus. We examine entrainment in use of high-frequency words (the most common words in the corpus), and its association with dialogue naturalness and flow, as well as with task success. Our results show that such entrainment is predictive of the perceived naturalness of dialogues and is significantly correlated with task success; in overall interaction flow, higher degrees of entrainment are associated with more overlaps and fewer interruptions.
  • Looked some more at the Cornel Toolkit, but it seems focussed on other conversation attributes, with more lexical analysis coming later
  • There is a github topic on discourse-analysis, of which John W. DuBois‘ rezonator project looks particularly interesting. Need to ask Wayne about how to reach out to someone like that.
    • Recently I’ve been interested in what happens when participants in conversation build off each other, reusing words, structures and other linguistic resources just used by a prior speaker. In dialogic syntax, as I call it, parallelism of structure across utterances foregrounds similarities in function, but also brings out differences. Participants notice even the subtlest contrasts in stance–epistemic, affective, illocutionary, and so on–generated by the resonance between juxtaposed utterances. The theories of dialogic syntax and stance are closely related, and I’m currently working on exploring this linkage–one more example of figuring out how language works on multiple levels simultaneously, uniting structure, meaning, cognition, and social interaction.