A Graph-based Model of Contextual Information in Sentiment Analysis over Twitter

English. Analyzing the sentiment expressed by short messages available in Social Media is challenging as the information when considering an instance is scarce. A fundamental role is played by Contextual information that is available when interpreting a message. In this paper, a Graph-based method is applied: a graph is built containing the contextual information needed to model complex interactions between messages. A Label Propagation algorithm is adopted to spread polarity information from known polarized nodes to the others. Italiano. Uno dei principali problemi nella analisi delle opinioni nei Social Media riguarda la quantitá di informazione utile che un singolo messaggio puó fornire. Il contesto di un messaggio costituisce un insieme di informazioni utile ad ovviare questo problema per la classificazione della polaritá. In questo articolo proponiamo di rappresentare le interazioni tra i messaggi in grafi che sono poi utilizzati in algoritmi di Label Propagation per diffondere la polaritá tra i nodi.

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