Anzeige
Erschienen in:
2014 | OriginalPaper | Buchkapitel
Understanding Online Social Networks’ Users – A Twitter Approach
verfasst von : Camelia Delcea, Liviu-Adrian Cotfas, Ramona Paun
Erschienen in: Computational Collective Intelligence. Technologies and Applications
Verlag: Springer International Publishing
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Twitter messages, also known as tweets, are increasingly used by marketers worldwide to determine consumer sentiments towards brands, products or events. Currently, most existing approaches used for social networks sentiment analysis only extract simple feedbacks in terms of positive and negative perception. In this paper, TweetOntoSense is proposed - a semantic based approach that uses ontologies in order to infer the actual user’s emotions. The extracted sentiments are described using a WordNet enriched emotional categories ontology. Thus, feelings such as happiness, affection, surprise, anger, sadness, etc. are put forth. Moreover, compared to existing approaches, TweetOntoSense also takes into consideration the fact that a single tweet message might express several, rather than a single emotion. A case study on Twitter is performed, also showing this approach’s practical applicability.