Item does not contain fulltextThis dataset features information on all the events that were automatically extracted from Twitter and used as input to periodicity detection, as described in the paper: F. Kunneman and A. Van den Bosch (2015), Automatically identifying periodic social events from Twitter, Proceedings of the RANLP 2015 (pp. 320-328), http://hdl.handle.net/2066/143994 The paper describes approaches to identifying periodic events in Twitter. This dataset contains the output of these approaches, as well as a human assessment of the quality of a selection of the output. Apart from information on all the events, tweet ids are shared that can be used to query the tweets and all their meta-data from Twitter
The important class of regularities that exist in a time series is nothing but the Partial periodic ...
Event detection on Twitter has become a promising research direction due to Twitter\u27s popularity,...
Containing tweet details of messages posted in Twitter related to diverse topics. These can be mined...
This dataset features information on all the events that were automatically extracted from Twitter a...
Item does not contain fulltextThis dataset features the output of intermediate steps and the final o...
Input data and output of research conducted in the study described in the paper: F. Kunneman and A....
Item does not contain fulltextThis directory features data that is discussed in the paper: F. Kunnem...
Many events referred to on Twitter are of a periodic nature, characterized by roughly constant time ...
Item does not contain fulltextThis dataset features the training models, emotion classifications and...
Item does not contain fulltextThis dataset features all the tweetids and labels that were used to mo...
This dataset was used in the manuscript "Scaling laws and dynamics of hashtags on Twitter".. The Tw...
A vast amount of textual web streams is influenced by events or phenomena emerging in the real world...
Copyright © 2015 Duc-Thuan Vo et al. This is an open access article distributed under the Creative C...
This dataset contains daily tweets ids during April 2013. This is provided to facilitate reproducibi...
The important class of regularities that exist in a time series is nothing but the Partial periodic ...
Event detection on Twitter has become a promising research direction due to Twitter\u27s popularity,...
Containing tweet details of messages posted in Twitter related to diverse topics. These can be mined...
This dataset features information on all the events that were automatically extracted from Twitter a...
Item does not contain fulltextThis dataset features the output of intermediate steps and the final o...
Input data and output of research conducted in the study described in the paper: F. Kunneman and A....
Item does not contain fulltextThis directory features data that is discussed in the paper: F. Kunnem...
Many events referred to on Twitter are of a periodic nature, characterized by roughly constant time ...
Item does not contain fulltextThis dataset features the training models, emotion classifications and...
Item does not contain fulltextThis dataset features all the tweetids and labels that were used to mo...
This dataset was used in the manuscript "Scaling laws and dynamics of hashtags on Twitter".. The Tw...
A vast amount of textual web streams is influenced by events or phenomena emerging in the real world...
Copyright © 2015 Duc-Thuan Vo et al. This is an open access article distributed under the Creative C...
This dataset contains daily tweets ids during April 2013. This is provided to facilitate reproducibi...
The important class of regularities that exist in a time series is nothing but the Partial periodic ...
Event detection on Twitter has become a promising research direction due to Twitter\u27s popularity,...
Containing tweet details of messages posted in Twitter related to diverse topics. These can be mined...