A USC Information Sciences Institute system pulls answers from online conversations by identifying the alpha chatterers.
The ISI study characterized online posts according a schema of speech acts. While some speech-act characterization was done by hand in this study to test the results, the ISI group has already developed effective software to accomplish the task automatically. (Credit: USC Information Sciences Institute)
The system, to be presented at a conference on human language technology on June 6, was developed to analyze technical conversations in which an objectively correct answer exists. But the method for statistically characterizing response by the group to individuals is generalizable.
Online communities are now firmly established in domains ranging from high school gossip to professional open-source software design discussions, generating huge repositories of records of human knowledge processing, pre-converted to digital form.
Such sites provide raw material for a new method that may, among other things, enable Internet chat room users to get a statistical measurement of their influence in their room.
This research is one of the first quantitative studies in the field of natural language processing that takes account of the fact that chat conversations are structured interactions among a large number of people.
In the long term, research in this area will lead to the development of systems that can automatically produce reports and summaries of meetings, researchers hope.