Publication | Closed Access
Building a conversational model from two-tweets
14
Citations
13
References
2011
Year
Unknown Venue
EngineeringSpoken Dialog SystemCommunicationCorpus LinguisticsText MiningNatural Language ProcessingComputational Social ScienceSocial MediaData ScienceComputational LinguisticsConversation AnalysisSingle InteractionLong ConversationsMachine TranslationDialogue ManagementConversational Recommender SystemConversational ModelSocial Medium DataArts
The current problem in building a conversational model from Twitter data is the scarcity of long conversations. According to our statistics, more than 90% of conversations in Twitter are composed of just two tweets. Previous work has utilized only conversations lasting longer than three tweets for dialogue modeling so that more than a single interaction can be successfully modeled. This paper verifies, by experiment, that two-tweet exchanges alone can lead to conversational models that are comparable to those made from longer-tweet conversations. This finding leverages the value of Twitter as a dialogue corpus and opens the possibility of better conversational modeling using Twitter data.
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