@article{editorial-gsi-article-2018,
author = "Iglesias, Carlos A. and Viviana Patti",
abstract = "Social networks are becoming more and more present in our daily lives. According to the Global Web Index, digital consumers spend an average of 2 h a day on social media and messaging. Thus, a large body of research has been developed in recent years to automatically process social media and social networks, with the aim of understanding, discovering insights into, and exploiting this information. All of this has contributed to the development of research areas such as sentiment analysis and social network analysis. The new communication media offer a unique opportunity to observe “in the wild” feelings and reactions spontaneously expressed on different topics, often using figurative language: sarcastic messages can be those that spread more virulently.
Nowadays, the focus of research is moving from polarity classification to more advanced and fine-grained aspects that can reveal insights into users’ emotions or personality traits or into their specific stance towards a target in online political debates, for which the presence of hate speech is also an important issue to monitor for preventing interference with other rights and the occasioning of certain harms. The temporal evolution of opinions in online communities is also a significant research topic that calls for a combination of sentiment and social network analysis techniques. This special issue includes three contributions that analyze strong feelings, such as love or hate, in social media and social networks, which are briefly described below.",
awards = "SJR Q3 (0.22)",
comments = "SJR 2018 Q3 0.222, Scopus 2018 Q3 1.7",
doi = "10.3390/info9080185",
issn = "2078-2489",
journal = "Information",
keywords = "love;hate;sentiment analysis;emotion analysis",
month = "July",
note = "SJR Q3 (0.22)",
number = "8",
pages = "184",
title = "{E}ditorial for the {S}pecial {I}ssue on “{L}ove {\&} {H}ate in the {T}ime of {S}ocial {M}edia and {S}ocial {N}etwork",
url = "http://www.mdpi.com/journal/information/special_issues/opinion_mining",
volume = "9",
year = "2018",
}