Emotional message-exchanges during 18 crisis events
This dataset is a set of eighteen directed networks that represents message exchanges among Twitter accounts during eighteen crisis events. The dataset comprises 645,339 anonymized unique user IDs and 1,396,709 edges that are labeled with respect to Plutchik's basic emotions (anger, fear, sadness, disgust, joy, trust, anticipation, and surprise) or "neutral" (if a tweet conveys no emotion).
The dataset was prepared in three steps: 1) We collected publicly available Twitter messages (tweets) related to eighteen different crisis events (nine natural disasters, four riots, five shooting and terror attacks) that happened in 2017 and 2018. 2) We labeled all messages with respect to the dominant emotion according to Plutchik's wheel of emotions (anger, anticipation, disgust, fear, joy, sadness, surprise, trust, or neutral). The emotion-labeling procedure uses the NRC word-emotion lexicon, the AFINN lexicon of affect, and a set of heuristics that people naturally use when detecting emotions in written texts (downtoners, boosters, emojis, negation, etc.). 3) We derived a directed communication network. Further details can be found in the README file that comes with the dataset.
Some findings related to this dataset have been published in the papers listed below. Please cite our papers when you use our network dataset:
 E. Kušen, M. Strembeck: You talkin' to me? Exploring Human/Bot Communication Patterns during Riot Events, In: Information Processing & Management (IPM), Vol. 57, No. 1, January 2020 https://doi.org/10.1016/j.ipm.2019.102126
 E. Kušen, M. Strembeck: Something draws near, I can feel it: An Analysis of Human and Bot Emotion-exchange Motifs on Twitter, In: Online Social Networks and Media (OSNEM), Vol. 10-11, May 2019 https://doi.org/10.1016/j.osnem.2019.04.001
 E. Kušen, M. Strembeck: An Analysis of Emotion-exchange Motifs in Multiplex Networks during Emergency Events, In: Applied Network Science (ANS), Vol. 4, March 2019 https://doi.org/10.1007/s41109-019-0115-6
Ema Kusen firstname.lastname@example.org
Mark Strembeck email@example.com