The web is composed of a multitude of sources. The differences between these sources are as vast as night and day. There are some key differences among them, and an accurate understanding of what they are can help to define more efficient ways to analyze the rich information they contain. This chapter introduces the psychological and sociological processes underlying social network interactions, which will be discussed within the framework of relevant theoretical constructs and methods of analysis (with a special focus on social network analysis). This chapter will highlight the differences and specific features that characterize online social network dynamics and then point out how this understanding can be effectively integrated into traditional sentiment analysis methodological approaches to empower their reliability and validity.

Pallavicini, F., Cipresso, P., Mantovani, F. (2017). Beyond Sentiment: How Social Network Analytics Can Enhance Opinion Mining and Sentiment Analysis. In Sentiment Analysis in Social Network (pp. 13-29). Elsevier Inc. [10.1016/B978-0-12-804412-4.00002-4].

Beyond Sentiment: How Social Network Analytics Can Enhance Opinion Mining and Sentiment Analysis

PALLAVICINI, FEDERICA
Primo
;
MANTOVANI, FABRIZIA
Ultimo
2017

Abstract

The web is composed of a multitude of sources. The differences between these sources are as vast as night and day. There are some key differences among them, and an accurate understanding of what they are can help to define more efficient ways to analyze the rich information they contain. This chapter introduces the psychological and sociological processes underlying social network interactions, which will be discussed within the framework of relevant theoretical constructs and methods of analysis (with a special focus on social network analysis). This chapter will highlight the differences and specific features that characterize online social network dynamics and then point out how this understanding can be effectively integrated into traditional sentiment analysis methodological approaches to empower their reliability and validity.
Capitolo o saggio
Computer-mediated communication; Facebook; Online communication; Opinion mining; Social media; social network analytics; Social networks; Twitter;
Online communication; Computer-mediated communication; Social networks; Social media; Social network Analytics; Opinion mining; Facebook; Twitter
English
Sentiment Analysis in Social Network
2017
9780128044124
Elsevier Inc.
13
29
Pallavicini, F., Cipresso, P., Mantovani, F. (2017). Beyond Sentiment: How Social Network Analytics Can Enhance Opinion Mining and Sentiment Analysis. In Sentiment Analysis in Social Network (pp. 13-29). Elsevier Inc. [10.1016/B978-0-12-804412-4.00002-4].
none
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/154794
Citazioni
  • Scopus 11
  • ???jsp.display-item.citation.isi??? 6
Social impact