Affect Analysis of Radical Contents on Web Forums Using SentiWordNet

The internet has become a major tool for communication, training, fundraising, media operations, and recruitment, and these processes often use web forums. This paper presents a model that was built using SentiWordNet, WordNet and NLTK to analyze selected web forums that included radical content. SentiWordNet is a lexical resource for supporting opinion mining by assigning a positivity score and a negativity score to each WordNet. The approaches of the model measure and identify sentiment polarity and affect the intensity of that which appears in the web forum. The results show that SentiWordNet can be used for analyzing sentences that appear in web forums

Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline

The Metabolism and Growth of Web Forums

We view web forums as virtual living organisms feeding on user's attention and investigate how these organisms grow at the expense of collective attention. We find that the "body mass" ($PV$) and "energy consumption" ($UV$) of the studied forums exhibits the allometric growth property, i.e., $PV_t \sim UV_t ^ \theta$. This implies that within a forum, the network transporting attention flow between threads has a structure invariant of time, despite of the continuously changing of the nodes (threads) and edges (clickstreams). The observed time-invariant topology allows us to explain the dynamics of networks by the behavior of threads. In particular, we describe the clickstream dissipation on threads using the function $D_i \sim T_i ^ \gamma$, in which $T_i$ is the clickstreams to node $i$ and $D_i$ is the clickstream dissipated from $i$. It turns out that $\gamma$, an indicator for dissipation efficiency, is negatively correlated with $\theta$ and $1/\gamma$ sets the lower boundary for $\theta$. Our findings have practical consequences. For example, $\theta$ can be used as a measure of the "stickiness" of forums, because it quantifies the stable ability of forums to convert $UV$ into $PV$, i.e., to remain users "lock-in" the forum. Meanwhile, the correlation between $\gamma$ and $\theta$ provides a convenient method to evaluate the `stickiness" of forums. Finally, we discuss an optimized "body mass" of forums at around $10^5$ that minimizes $\gamma$ and maximizes $\theta$.Comment: 6 figure

Negative emotions boost users activity at BBC Forum

We present an empirical study of user activity in online BBC discussion forums, measured by the number of posts written by individual debaters and the average sentiment of these posts. Nearly 2.5 million posts from over 18 thousand users were investigated. Scale free distributions were observed for activity in individual discussion threads as well as for overall activity. The number of unique users in a thread normalized by the thread length decays with thread length, suggesting that thread life is sustained by mutual discussions rather than by independent comments. Automatic sentiment analysis shows that most posts contain negative emotions and the most active users in individual threads express predominantly negative sentiments. It follows that the average emotion of longer threads is more negative and that threads can be sustained by negative comments. An agent based computer simulation model has been used to reproduce several essential characteristics of the analyzed system. The model stresses the role of discussions between users, especially emotionally laden quarrels between supporters of opposite opinions, and represents many observed statistics of the forum.Comment: 29 pages, 6 figure