The Higgs dataset has been built after monitoring the spreading processes on Twitter before, during and after the announcement of the discovery of a new particle with the features of the elusive Higgs boson on 4th July 2012. The messages posted in Twitter about this discovery between 1st and 7th July 2012 are considered.
The four directional networks made available here have been extracted from user activities in Twitter as:
It is worth remarking that the user IDs have been anonimized, and the same user ID is used for all networks. This choice allows to use the Higgs dataset in studies about large-scale interdependent/interconnected multiplex/multilayer networks, where one layer accounts for the social structure and three layers encode different types of user dynamics .
Note that this dataset has been updated on Mar 31 2015. If you downloaded a previous version, please update it, results could differ.
For more information about data collection, please refer to our paper.
Dataset statistics are calculated for the graph with the highest number of nodes and edges:
|Social Network statistics|
|Nodes in largest WCC||456290 (0.999)|
|Edges in largest WCC||14855466 (1.000)|
|Nodes in largest SCC||360210 (0.789)|
|Edges in largest SCC||14102605 (0.949)|
|Average clustering coefficient||0.1887|
|Number of triangles||83023401|
|Fraction of closed triangles||0.002901|
|Diameter (longest shortest path)||9|
|90-percentile effective diameter||3.7|
|Retweet Network statistics|
|Nodes in largest WCC||223833 (0.873)|
|Edges in largest WCC||308596 (0.940)|
|Nodes in largest SCC||984 (0.004)|
|Edges in largest SCC||3850 (0.012)|
|Average clustering coefficient||0.0156|
|Number of triangles||21172|
|Fraction of closed triangles||0.0001085|
|Diameter (longest shortest path)||19|
|90-percentile effective diameter||6.8|
|Reply Network statistics|
|Nodes in largest WCC||12839 (0.330)|
|Edges in largest WCC||14944 (0.459)|
|Nodes in largest SCC||322 (0.008)|
|Edges in largest SCC||708 (0.022)|
|Average clustering coefficient||0.0058|
|Number of triangles||244|
|Fraction of closed triangles||0.0001561|
|Diameter (longest shortest path)||29|
|90-percentile effective diameter||10|
|Mention Network statistics|
|Nodes in largest WCC||91606 (0.787)|
|Edges in largest WCC||132068 (0.876)|
|Nodes in largest SCC||1801 (0.015)|
|Edges in largest SCC||7069 (0.047)|
|Average clustering coefficient||0.0825|
|Number of triangles||23068|
|Fraction of closed triangles||0.0002417|
|Diameter (longest shortest path)||18|
|90-percentile effective diameter||6.5|
Interaction can be RT (retweet), MT (mention) or RE (reply). Each link is directed. The user IDs in this dataset corresponds to the ones adopted to anonymize the social structure, thus the datasets (1) - (5) can be used together for complex analysis involving structure and dynamics.
Note 1: the direction of links depends on the application, in general. For instance, if one is interested in building a network of how information flows, then the direction of RT should be reversed when used in the analysis. Nevertheless, the choice is left to the researcher and his/her own interpretation of the data, whereas we just provide the observed actions, i.e., who retweets/mentions/replies/follows whom.
Note 2: users mentioned in retweeted tweets are considered as mentions. For instance, if @A retweets the tweet “hello @C @D" sent by @B, then the following links are created: @A @B timeX RT, @A @C timeX MT, @A @D timeX MT, because @C and @D can be notified that they have been mentioned in a retweet. Similarly in the case of a reply. If for some reason the researcher does not agree with this choice, he/she can easily identify this type of links and remove the mentions, for instance.
|social_network.edgelist.gz||Friends/follower graph (directed)|
|retweet_network.edgelist.gz||Graph of who retweets whom (directed and weighted)|
|reply_network.edgelist.gz||Graph of who replies to who (directed and weighted)|
|mention_network.edgelist.gz||Graph of who mentions whom (directed and weighted)|
|higgs-activity_time.txt.gz||The dataset provides information about activity on Twitter during the discovery of Higgs boson|