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We describe a method for discovering irregularities in temporal mood patterns appearing in a large corpus of blog posts, and labeling them with a natural language explanation. Simple techniques based on comparing corpus frequencies, coupled with large quantities of data, are shown to be effective for identifying the events underlying changes in global moods.
Mood classification for blogs is useful in helping user-to-agent interaction for a variety of applic...
Understanding the causes of spikes in the emotion flow of influential social media users is a key co...
Using a total of 20 million mood-annotated blog posts harvested between June 2005 and March 2006, we...
The personal, diary-like nature of blogs prompts many bloggers to indicate their mood at the time of...
The personal, diary-like nature of blogs prompts many blog-gers to indicate their mood at the time o...
A convergence of emotions among people in social networks is potentially resulted by the occurrence ...
We demonstrate a system for tracking and analyzing moods of bloggers worldwide, as reflected in the ...
Automatic data-driven analysis of mood from text is anemerging problem with many potential applicati...
Significant world events often cause the behavioral convergence of the expression of shared sentimen...
We present a large-scale mood analysis in social media texts. We organise the paper in three parts: ...
Abstract. As an effort to detect the mood of a blog, regardless of the length and writing style, we ...
Abstract. Automatic data-driven analysis of mood from text is an emerging problem with many potentia...
One of the goals of affective computing is to recognize human emotions. We present a system that lea...
Abstract We present a large-scale mood analysis in social media texts. We organize the paper in thre...
Mood classification for blogs is useful in helping user-to-agent interaction for a variety of applic...
Mood classification for blogs is useful in helping user-to-agent interaction for a variety of applic...
Understanding the causes of spikes in the emotion flow of influential social media users is a key co...
Using a total of 20 million mood-annotated blog posts harvested between June 2005 and March 2006, we...
The personal, diary-like nature of blogs prompts many bloggers to indicate their mood at the time of...
The personal, diary-like nature of blogs prompts many blog-gers to indicate their mood at the time o...
A convergence of emotions among people in social networks is potentially resulted by the occurrence ...
We demonstrate a system for tracking and analyzing moods of bloggers worldwide, as reflected in the ...
Automatic data-driven analysis of mood from text is anemerging problem with many potential applicati...
Significant world events often cause the behavioral convergence of the expression of shared sentimen...
We present a large-scale mood analysis in social media texts. We organise the paper in three parts: ...
Abstract. As an effort to detect the mood of a blog, regardless of the length and writing style, we ...
Abstract. Automatic data-driven analysis of mood from text is an emerging problem with many potentia...
One of the goals of affective computing is to recognize human emotions. We present a system that lea...
Abstract We present a large-scale mood analysis in social media texts. We organize the paper in thre...
Mood classification for blogs is useful in helping user-to-agent interaction for a variety of applic...
Mood classification for blogs is useful in helping user-to-agent interaction for a variety of applic...
Understanding the causes of spikes in the emotion flow of influential social media users is a key co...
Using a total of 20 million mood-annotated blog posts harvested between June 2005 and March 2006, we...
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