The personal, diary-like nature of blogs prompts many blog-gers to indicate their mood at the time of posting. Aggregat-ing these indications over a large amount of bloggers gives a “blogosphere state-of-mind ” for each point in time: the inten-sity of different moods among bloggers at that time. In this paper, we address the task of estimating this state-of-mind from the text written by bloggers. To this end, we build mod-els that predict the levels of various moods according to the language used by bloggers at a given time; our models show high correlation with the moods actually measured, and sub-stantially outperform a baseline
Automatic data-driven analysis of mood from text is anemerging problem with many potential applicati...
A convergence of emotions among people in social networks is potentially resulted by the occurrence ...
Sentiment analysis is a field of computational linguistics involving identification, ex-traction, an...
The personal, diary-like nature of blogs prompts many bloggers to indicate their mood at the time of...
We describe a method for discovering irregularities in temporal mood patterns appearing in a large c...
We demonstrate a system for tracking and analyzing moods of bloggers worldwide, as reflected in the ...
We present a large-scale mood analysis in social media texts. We organise the paper in three parts: ...
One of the goals of affective computing is to recognize human emotions. We present a system that lea...
Abstract. As an effort to detect the mood of a blog, regardless of the length and writing style, we ...
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...
Using a total of 20 million mood-annotated blog posts harvested between June 2005 and March 2006, we...
Significant world events often cause the behavioral convergence of the expression of shared sentimen...
Abstract. Automatic data-driven analysis of mood from text is an emerging problem with many potentia...
Automatic data-driven analysis of mood from text is anemerging problem with many potential applicati...
A convergence of emotions among people in social networks is potentially resulted by the occurrence ...
Sentiment analysis is a field of computational linguistics involving identification, ex-traction, an...
The personal, diary-like nature of blogs prompts many bloggers to indicate their mood at the time of...
We describe a method for discovering irregularities in temporal mood patterns appearing in a large c...
We demonstrate a system for tracking and analyzing moods of bloggers worldwide, as reflected in the ...
We present a large-scale mood analysis in social media texts. We organise the paper in three parts: ...
One of the goals of affective computing is to recognize human emotions. We present a system that lea...
Abstract. As an effort to detect the mood of a blog, regardless of the length and writing style, we ...
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...
Using a total of 20 million mood-annotated blog posts harvested between June 2005 and March 2006, we...
Significant world events often cause the behavioral convergence of the expression of shared sentimen...
Abstract. Automatic data-driven analysis of mood from text is an emerging problem with many potentia...
Automatic data-driven analysis of mood from text is anemerging problem with many potential applicati...
A convergence of emotions among people in social networks is potentially resulted by the occurrence ...
Sentiment analysis is a field of computational linguistics involving identification, ex-traction, an...