Add to ORKGUsing a total of 20 million mood-annotated blog posts harvested between June 2005 and March 2006, we provide a time series analysis of the number of blog posts annotated with a mood. State-space methods are used to determine decompositions of the time series data associated with bloggers ' moods (either individual or aggegrated), allowing us to look for patterns of trend, seasonality and cycle
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...
Abstract. As an effort to detect the mood of a blog, regardless of the length and writing style, 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...
Sentiment analysis predicts a one-dimensional quantity describing the positive or negative emotion o...
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 ...
Significant world events often cause the behavioral convergence of the expression of shared sentimen...
In this work, we investigated the social media streams to understand their characteristics and their...
We present a large-scale mood analysis in social media texts. We organise the paper in three parts: ...
(A) Each emotional dynamics Zk(t) Tension, Depression, Anger, Vigor, Fatigue, and Confusion are show...
A convergence of emotions among people in social networks is potentially resulted by the occurrence ...
We have developed a computational framework to characterize social network dynamics in the blogosphe...
Trend information is a summarization of temporal statistical data, such as changes in product prices...
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...
Abstract. As an effort to detect the mood of a blog, regardless of the length and writing style, 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...
Sentiment analysis predicts a one-dimensional quantity describing the positive or negative emotion o...
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 ...
Significant world events often cause the behavioral convergence of the expression of shared sentimen...
In this work, we investigated the social media streams to understand their characteristics and their...
We present a large-scale mood analysis in social media texts. We organise the paper in three parts: ...
(A) Each emotional dynamics Zk(t) Tension, Depression, Anger, Vigor, Fatigue, and Confusion are show...
A convergence of emotions among people in social networks is potentially resulted by the occurrence ...
We have developed a computational framework to characterize social network dynamics in the blogosphe...
Trend information is a summarization of temporal statistical data, such as changes in product prices...
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...
Abstract. As an effort to detect the mood of a blog, regardless of the length and writing style, we ...