Advances in Social Media Analysis [[electronic resource] /] / edited by Mohamed Medhat Gaber, Mihaela Cocea, Nirmalie Wiratunga, Ayse Goker

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015
• Edizione: 1st ed. 2015.
• Descrizione fisica: 1 online resource (VII, 151 p. 29 illus.)
• Disciplina: 302.231
• Soggetto topico: Computational intelligence; Artificial intelligence; Computational Intelligence; Artificial Intelligence
• Persona (resp. second.): GaberMohamed Medhat; CoceaMihaela; WiratungaNirmalie; GokerAyse
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di contenuto: Case-Studies in Mining User-Generated Reviews for Recommendation -- Mining Newsworthy Topics from Social Media -- Sentiment Analysis Using Supervised Learning with Domain-Adaptation and Sentence-Based Analysis -- Pattern-based Emotion Classification on Social Media -- Entity-based Opinion Mining from Text and Multimedia -- Predicting Emotion Labels for Chinese Microblog Texts.
• Sommario/riassunto: This volume presents a collection of carefully selected contributions in the area of social media analysis. Each chapter opens up a number of research directions that have the potential to be taken on further in this rapidly growing area of research. The chapters are diverse enough to serve a number of directions of research with Sentiment Analysis as the dominant topic in the book. The authors have provided a broad range of research achievements from multimodal sentiment identification to emotion detection in a Chinese microblogging website. The book will be useful to research students, academics and practitioners in the area of social media analysis. .
• Titolo autorizzato: Advances in Social Media Analysis
• ISBN: 3-319-18458-X
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910299822403321
• Lo trovi qui: Univ. Federico II
• Serie: Studies in Computational Intelligence, . 1860-949X ; ; 602