DOI | Trouver le DOI : https://doi.org/10.1145/2502069.2502070 |
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Auteur | Rechercher : Mohammad, S.M.1; Rechercher : Kiritchenko, S.1; Rechercher : Martin, J.1 |
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Affiliation | - Conseil national de recherches du Canada
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Format | Texte, Article |
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Conférence | 2nd International Workshop on Issues of Sentiment Discovery and Opinion Mining, WISDOM 2013 - Held in Conjunction with SIGKDD 2013, 11 August 2013 through 11 August 2013, Chicago, IL |
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Sujet | Emotion detection; Key Issues; Large dataset; National elections; Natural language applications; Question Answering; Single event; Data mining; Natural language processing systems |
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Résumé | Tweets pertaining to a single event, such as a national election, can number in the hundreds of millions. Automatically analyzing them is beneficial in many downstream natural language applications such as question answering and summarization. In this paper, we propose a new task: identifying purpose behind electoral tweets|why do people post election-oriented tweets? We show that identifying purpose is related to sentiment and emotion detection, but yet significantly different. Detecting purpose has a number of applications including detecting the mood of the electorate, estimating the popularity of policies, identifying key issues of contention, and predicting the course of events. We create a large dataset of electoral tweets and annotate a few thousand tweets for purpose. We develop a system that automatically classifies electoral tweets as per their purpose, obtaining an accuracy of 44.58% on an 11-class task and an accuracy of 73.91% on a 3-class task (both accuracies well above the most-frequent-class baseline). We also show that resources developed for emotion detection are helpful for detecting purpose. |
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Date de publication | 2013 |
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Dans | |
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Langue | anglais |
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Publications évaluées par des pairs | Oui |
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Numéro NPARC | 21270890 |
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Exporter la notice | Exporter en format RIS |
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Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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Identificateur de l’enregistrement | 34fa28d6-df63-4377-abcd-fb224ccefc0f |
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Enregistrement créé | 2014-02-18 |
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Enregistrement modifié | 2020-04-22 |
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