Detecting Happiness in Italian Tweets: Towards an Evaluation Dataset for Sentiment Analysis in Felicittà

CRISTINA BOSCO, LEONARDO ALLISIO, V. Mussa, PATTI Viviana, Giancarlo Francesco RUFFO, MANUELA SANGUINETTI, EMILIO SULIS

Risultato della ricerca: Contributo alla conferenzaContributo in Atti di Convegnopeer review

Abstract

This paper focuses on the development of a gold standard corpus for the validation of Felicitta, an online platform which uses Twitter as data source in order to estimate and interactively display the degree of happiness in the Italian cities. The ultimate goal is the creation of an Italian reference Twitter dataset for sentiment analysis that can be used in several frameworks aimed at detecting sentiment from big data sources. We will provide an overview of the reference corpus created for evaluating Felicitta, with a special focus on the issues ` raised from its development, on the inter-annotator agreement discussion and on implications for the further development of the corpus, considering that the assumption that a single right answer exists for each annotated instance cannot be done in several cases in the particular kind of data at issue.
Lingua originaleInglese
Pagine56-63
Numero di pagine8
Stato di pubblicazionePubblicato - 1 gen 2014
Evento5th International Workshop on EMOTION, SOCIAL SIGNALS, SENTIMENT & LINKED OPEN DATA, ES³LOD 2014 - Reykjavik, Islanda
Durata: 1 gen 2014 → …

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???event.eventtypes.event.conference???5th International Workshop on EMOTION, SOCIAL SIGNALS, SENTIMENT & LINKED OPEN DATA, ES³LOD 2014
CittàReykjavik, Islanda
Periodo1/01/14 → …

Keywords

  • sentiment analysis
  • twitter
  • social media
  • corpus annotation

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