29,313 research outputs found
Better Document-level Sentiment Analysis from RST Discourse Parsing
Discourse structure is the hidden link between surface features and
document-level properties, such as sentiment polarity. We show that the
discourse analyses produced by Rhetorical Structure Theory (RST) parsers can
improve document-level sentiment analysis, via composition of local information
up the discourse tree. First, we show that reweighting discourse units
according to their position in a dependency representation of the rhetorical
structure can yield substantial improvements on lexicon-based sentiment
analysis. Next, we present a recursive neural network over the RST structure,
which offers significant improvements over classification-based methods.Comment: Published at Empirical Methods in Natural Language Processing (EMNLP
2015
Topic Independent Identification of Agreement and Disagreement in Social Media Dialogue
Research on the structure of dialogue has been hampered for years because
large dialogue corpora have not been available. This has impacted the dialogue
research community's ability to develop better theories, as well as good off
the shelf tools for dialogue processing. Happily, an increasing amount of
information and opinion exchange occur in natural dialogue in online forums,
where people share their opinions about a vast range of topics. In particular
we are interested in rejection in dialogue, also called disagreement and
denial, where the size of available dialogue corpora, for the first time,
offers an opportunity to empirically test theoretical accounts of the
expression and inference of rejection in dialogue. In this paper, we test
whether topic-independent features motivated by theoretical predictions can be
used to recognize rejection in online forums in a topic independent way. Our
results show that our theoretically motivated features achieve 66% accuracy, an
improvement over a unigram baseline of an absolute 6%.Comment: @inproceedings{Misra2013TopicII, title={Topic Independent
Identification of Agreement and Disagreement in Social Media Dialogue},
author={Amita Misra and Marilyn A. Walker}, booktitle={SIGDIAL Conference},
year={2013}
Linguistic Harbingers of Betrayal: A Case Study on an Online Strategy Game
Interpersonal relations are fickle, with close friendships often dissolving
into enmity. In this work, we explore linguistic cues that presage such
transitions by studying dyadic interactions in an online strategy game where
players form alliances and break those alliances through betrayal. We
characterize friendships that are unlikely to last and examine temporal
patterns that foretell betrayal.
We reveal that subtle signs of imminent betrayal are encoded in the
conversational patterns of the dyad, even if the victim is not aware of the
relationship's fate. In particular, we find that lasting friendships exhibit a
form of balance that manifests itself through language. In contrast, sudden
changes in the balance of certain conversational attributes---such as positive
sentiment, politeness, or focus on future planning---signal impending betrayal.Comment: To appear at ACL 2015. 10pp, 4 fig. Data and other info available at
http://vene.ro/betrayal
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