Georgia Tech at EMNLP 2015

Georgia Tech is presenting four papers at EMNLP 2015 in Lisbon!

  • One Vector is not Enough: Entity-Augmented Distributed Semantics for Discourse Relations. Yangfeng Ji and Jacob Eisenstein (published in the Transactions of Computational Linguistics). This paper presents a distributed semantics approach to discourse relation classification, computing representations for discourse arguments and entities through recursive neural networks.
  • Confounds and Consequences in Geotagged Twitter Data. Umashanthi Pavalanathan and Jacob Eisenstein (full paper). GPS-tagged Twitter data is used widely in social media analysis, but relatively little is understood about the biases that it contains. This paper compares GPS-tagged tweets with messages that are located by user self-report, considering geographical location (urban core versus periphery), gender, age, and linguistic content. We find significant differences on all dimensions, and show that text-based author geolocation performs best on older, male authors.
  • Better Document-level Sentiment Analysis from RST Discourse ParsingParminder Bhatia, Yangfeng Ji, and Jacob Eisenstein (short paper). We present two models for using hierarchical discourse parses to improve document-level sentiment analysis, obtaining significant improvements over both lexicon-based and classification-based sentiment analyzers.
  • Closing the gap: Domain adaptation from explicit to implicit discourse relations. Yangfeng Ji, Gongbo Zhang, and Jacob Eisenstein (short paper). Discourse relations can be marked explicitly with connectors like “however” and “nonetheless”, but they are often implicit. We show how explicitly marked discourse relations can serve as a supervision signal towards automatically classifying implicitly-labeled discourse relations.

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