Detecting forum authority claims in online discussions

ABSTRACT

This paper explores the problem of detecting sentence-level forum authority claims in online discussions. Using a maximum entropy model, we explore a variety of strategies for extracting lexical features in a sparse training scenario, comparing knowledge- and data-driven methods (and combinations). The augmentation of lexical features with parse context is also investigated. We find that certain markup features perform remarkably well alone, but are outperformed by data-driven selection of lexical features augmented with parse context.

References

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Index Terms

• Applied computing

  • Arts and humanities

    • Language translation

• Computing methodologies

  • Artificial intelligence

    • Natural language processing

• Human-centered computing

  • Human computer interaction (HCI)

    • Interaction paradigms

      • Web-based interaction

• Information systems

  • Information retrieval

  • Information storage systems