717 research outputs found
Sentiment Analysis Of Web Forums: Comparison Between SentiWordNet And SentiStrength
Internet has become a major tool for communication, training, fundraising, media operations, and recruitment, and these processes often use web forums. This paper intended to find suitable technique for analysing selected web forums that included radical content by presenting a comparison between SentiWordNet and SentiStrength. SentiWordNet is a lexical resource for supporting opinion mining by assigning a positivity score and a negativity score to each WordNet. SentiStrength is a technique that was developed from comments on MySpace. It uses human-designed lexical and emotional terms with a set of amplification, diminishing and negation rules. The results have been presented and discussed
An Agent-Based Model of Collective Emotions in Online Communities
We develop a agent-based framework to model the emergence of collective
emotions, which is applied to online communities. Agents individual emotions
are described by their valence and arousal. Using the concept of Brownian
agents, these variables change according to a stochastic dynamics, which also
considers the feedback from online communication. Agents generate emotional
information, which is stored and distributed in a field modeling the online
medium. This field affects the emotional states of agents in a non-linear
manner. We derive conditions for the emergence of collective emotions,
observable in a bimodal valence distribution. Dependent on a saturated or a
superlinear feedback between the information field and the agent's arousal, we
further identify scenarios where collective emotions only appear once or in a
repeated manner. The analytical results are illustrated by agent-based computer
simulations. Our framework provides testable hypotheses about the emergence of
collective emotions, which can be verified by data from online communities.Comment: European Physical Journal B (in press), version 2 with extended
introduction, clarification
Emotions, Demographics and Sociability in Twitter Interactions
The social connections people form online affect the quality of information
they receive and their online experience. Although a host of socioeconomic and
cognitive factors were implicated in the formation of offline social ties, few
of them have been empirically validated, particularly in an online setting. In
this study, we analyze a large corpus of geo-referenced messages, or tweets,
posted by social media users from a major US metropolitan area. We linked these
tweets to US Census data through their locations. This allowed us to measure
emotions expressed in the tweets posted from an area, the structure of social
connections, and also use that area's socioeconomic characteristics in
analysis. %We extracted the structure of online social interactions from the
people mentioned in tweets from that area. We find that at an aggregate level,
places where social media users engage more deeply with less diverse social
contacts are those where they express more negative emotions, like sadness and
anger. Demographics also has an impact: these places have residents with lower
household income and education levels. Conversely, places where people engage
less frequently but with diverse contacts have happier, more positive messages
posted from them and also have better educated, younger, more affluent
residents. Results suggest that cognitive factors and offline characteristics
affect the quality of online interactions. Our work highlights the value of
linking social media data to traditional data sources, such as US Census, to
drive novel analysis of online behavior.Comment: International Conference on the Web and Social Media (ICWSM2016
Emotional persistence in online chatting communities
How do users behave in online chatrooms, where they instantaneously read and
write posts? We analyzed about 2.5 million posts covering various topics in
Internet relay channels, and found that user activity patterns follow known
power-law and stretched exponential distributions, indicating that online chat
activity is not different from other forms of communication. Analysing the
emotional expressions (positive, negative, neutral) of users, we revealed a
remarkable persistence both for individual users and channels. I.e. despite
their anonymity, users tend to follow social norms in repeated interactions in
online chats, which results in a specific emotional "tone" of the channels. We
provide an agent-based model of emotional interaction, which recovers
qualitatively both the activity patterns in chatrooms and the emotional
persistence of users and channels. While our assumptions about agent's
emotional expressions are rooted in psychology, the model allows to test
different hypothesis regarding their emotional impact in online communication.Comment: 34 pages, 4 main and 12 supplementary figure
- …