This dataset features all the tweetids and labels that were used to model the language of 24 hashtags, and test the performance on predicting the hashtags in unseen tweets. This study is described in: Kunneman, F.A., Liebrecht, C.C. & Bosch, A.P.J. van den (2014). The (Un)Predictability of Emotional Hashtags in Twitter. In Proceedings of the 5th Workshop on Language Analysis for Social Media (LASM) @ EACL 2014 (pp. 26-34). s.l.: Association for Computational Linguistics, http://hdl.handle.net/2066/127067 In addition to the train and test data, this dataset includes the most indicative features (words and phrases) for four of the hashtags, as well as the human judgement whether the tweets that contain or are classified with these hashtags ...
Social media has become an excellent way to discover people's thoughts about various topics and...
We demonstrate an approach to predict latent personal at-tributes including user demographics, onlin...
With the growing influence of social media platforms like Twitter, understanding and analyzing the s...
This dataset features all the tweetids and labels that were used to model the language of 24 hashtag...
This dataset features the training models, emotion classifications and emotion patterns before and a...
This dataset features training and test tweets as well as insights into the classifier model related...
Hashtags in Twitter posts may carry dif-ferent semantic payloads. Their dual form (word and label) m...
Affective computing is the study and development of devices that can recognize emotions through vari...
Input data and output of research conducted in the study described in the paper: F. Kunneman and A....
Detecting emotions in microblogs and social media posts has applications for industry, health, and s...
Twitter messages often contain so-called hashtags to denote keywords related to them. Using a datase...
This dataset features the output of intermediate steps and the final output of the research that is ...
Abstract — In this paper, we use machine learning techniques to try to find the best possible soluti...
The goal of this master thesis is to classify short Twitter messages with respect to their sentiment...
ABSTRACT: In the recent years, Social web mining has gained significant attention with case of it&qu...
Social media has become an excellent way to discover people's thoughts about various topics and...
We demonstrate an approach to predict latent personal at-tributes including user demographics, onlin...
With the growing influence of social media platforms like Twitter, understanding and analyzing the s...
This dataset features all the tweetids and labels that were used to model the language of 24 hashtag...
This dataset features the training models, emotion classifications and emotion patterns before and a...
This dataset features training and test tweets as well as insights into the classifier model related...
Hashtags in Twitter posts may carry dif-ferent semantic payloads. Their dual form (word and label) m...
Affective computing is the study and development of devices that can recognize emotions through vari...
Input data and output of research conducted in the study described in the paper: F. Kunneman and A....
Detecting emotions in microblogs and social media posts has applications for industry, health, and s...
Twitter messages often contain so-called hashtags to denote keywords related to them. Using a datase...
This dataset features the output of intermediate steps and the final output of the research that is ...
Abstract — In this paper, we use machine learning techniques to try to find the best possible soluti...
The goal of this master thesis is to classify short Twitter messages with respect to their sentiment...
ABSTRACT: In the recent years, Social web mining has gained significant attention with case of it&qu...
Social media has become an excellent way to discover people's thoughts about various topics and...
We demonstrate an approach to predict latent personal at-tributes including user demographics, onlin...
With the growing influence of social media platforms like Twitter, understanding and analyzing the s...