Modeling leadership and influence in multi-party online discourse

Tomek Strzalkowski, Samira Shaikh, Ting Liu, George Aaron Broadwell, Jenny Stromer-Galley, Sarah Taylor, Veena Ravishankar, Umit Boz, Xiaoai Ren

Research output: Contribution to conferencePaperpeer-review

8 Scopus citations


In this article, we present a novel approach towards the detection and modeling of complex social phenomena in multi-party discourse, including leadership, influence, pursuit of power and group cohesion. We have developed a two-tier approach that relies on observable and computable linguistic features of conversational text to make predictions about sociolinguistic behaviors such as Topic Control and Disagreement, that speakers deploy in order to achieve and maintain certain positions and roles in a group. These sociolinguistic behaviors are then used to infer higher-level social phenomena such as Leadership and Influence, which is the focus of this paper. We show robust performance results by comparing our automatically computed results to participants' own perceptions and rankings. We use weights learnt from correlations with training examples known leadership and influence rankings of participants to optimize our models and to show performance significantly above baseline for two different languages - English and Mandarin Chinese.

Original languageEnglish (US)
Number of pages18
StatePublished - 2012
Externally publishedYes
Event24th International Conference on Computational Linguistics, COLING 2012 - Mumbai, India
Duration: Dec 8 2012Dec 15 2012


Other24th International Conference on Computational Linguistics, COLING 2012


  • Computational sociolinguistics
  • Influence
  • Linguistic behavior
  • Multi-disciplinary artificial intelligence
  • Online dialogues
  • Social computing
  • Social phenomena

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Language and Linguistics
  • Linguistics and Language


Dive into the research topics of 'Modeling leadership and influence in multi-party online discourse'. Together they form a unique fingerprint.

Cite this