scispace - formally typeset
Open AccessJournal ArticleDOI

Collective emotions online and their influence on community life.

Reads0
Chats0
TLDR
The results prove that collective emotional states can be created and modulated via Internet communication and that emotional expressiveness is the fuel that sustains some e-communities.
Abstract
Background E-communities, social groups interacting online, have recently become an object of interdisciplinary research. As with face-to-face meetings, Internet exchanges may not only include factual information but also emotional information – how participants feel about the subject discussed or other group members. Emotions in turn are known to be important in affecting interaction partners in offline communication in many ways. Could emotions in Internet exchanges affect others and systematically influence quantitative and qualitative aspects of the trajectory of e-communities? The development of automatic sentiment analysis has made large scale emotion detection and analysis possible using text messages collected from the web. However, it is not clear if emotions in e-communities primarily derive from individual group members' personalities or if they result from intra-group interactions, and whether they influence group activities. Methodology/Principal Findings Here, for the first time, we show the collective character of affective phenomena on a large scale as observed in four million posts downloaded from Blogs, Digg and BBC forums. To test whether the emotions of a community member may influence the emotions of others, posts were grouped into clusters of messages with similar emotional valences. The frequency of long clusters was much higher than it would be if emotions occurred at random. Distributions for cluster lengths can be explained by preferential processes because conditional probabilities for consecutive messages grow as a power law with cluster length. For BBC forum threads, average discussion lengths were higher for larger values of absolute average emotional valence in the first ten comments and the average amount of emotion in messages fell during discussions. Conclusions/Significance Overall, our results prove that collective emotional states can be created and modulated via Internet communication and that emotional expressiveness is the fuel that sustains some e-communities.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

A survey of sentiment analysis in social media

TL;DR: A large quantity of techniques and methods are categorized and compared in the area of sentiment analysis, and different types of data and advanced tools for research are introduced, as well as their limitations.
Journal ArticleDOI

Opinion mining in social media: Modeling, simulating, and forecasting political opinions in the web

TL;DR: An opinion formation framework based on content analysis of social media and sociophysical system modeling is proposed, and three building blocks of online opinion tracking and simulation are described.
Journal ArticleDOI

Climate change on Twitter: topics, communities and conversations about the 2013 IPCC Working Group 1 report.

TL;DR: Twitter analysis suggested the emergence of a community of Twitter users, predominantly based in the UK, where greater interaction between contrasting views took place, and illustrated the presence of a campaign by the non-governmental organization Avaaz, aimed at increasing media coverage of the IPCC report.
Book ChapterDOI

The Heart and Soul of the Web? Sentiment Strength Detection in the Social Web with SentiStrength

TL;DR: This chapter describes the sentiment strength detection program SentiStrength that was developed during the CyberEmotions project to detect the strength of sentiments expressed in social web texts.
Journal ArticleDOI

Artemisinin as an anticancer drug: Recent advances in target profiling and mechanisms of action

TL;DR: The mechanism of artemisinin activation in cancer, novel and significant findings with regards to art Artemisinin target proteins and pathways, new understandings in artemisInin‐induced cell death mechanisms, as well as the practical issues of repurposing artemis inin are discussed.
References
More filters
Journal ArticleDOI

Emergence of Scaling in Random Networks

TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.

An Introduction To Probability Theory And Its Applications

TL;DR: A First Course in Probability (8th ed.) by S. Ross is a lively text that covers the basic ideas of probability theory including those needed in statistics.
Book

The Expression of the Emotions in Man and Animals

TL;DR: The Expression of the Emotions in Man and Animals Introduction to the First Edition and Discussion Index, by Phillip Prodger and Paul Ekman.
Related Papers (5)