TiDeH: Time-dependent Hawkes process for predicting retweet dynamics

Ryota Kobayashi, Renaud Lambiotte

Résultats de recherche: Contribution dans un livre/un catalogue/un rapport/dans les actes d'une conférenceArticle dans les actes d'une conférence/un colloque

Résumé

Online social networking services allow their users to post content in the form of text, images or videos. The main mechanism driving content diffusion is the possibility for users to re-share the content posted by their social connections, which may then cascade across the system. A fundamental problem when studying information cascades is the possibility to develop sound mathematical models, whose parameters can be calibrated on empirical data, in order to predict the future course of a cascade after a window of observation. In this paper, we focus on Twitter and, in particular, on the temporal patterns of retweet activity for an original tweet. We model the system by Time-Dependent Hawkes process (TiDeH), which properly takes into account the circadian nature of the users and the aging of information. The input of the prediction model are observed retweet times and structural information about the underlying social network. We develop a procedure for parameter optimization and for predicting the future profiles of retweet activity at different time resolutions. We validate our methodology on a large corpus of Twitter data and demonstrate its systematic improvement over existing approaches in all the time regimes.

langue originaleAnglais
titreProceedings of the 10th International Conference on Web and Social Media, ICWSM 2016
EditeurAAAI Press
Pages191-200
Nombre de pages10
ISBN (Electronique)9781577357582
étatPublié - 2016
Evénement10th International Conference on Web and Social Media, ICWSM 2016 - Cologne, Allemagne
Durée: 17 mai 201620 mai 2016

Une conférence

Une conférence10th International Conference on Web and Social Media, ICWSM 2016
PaysAllemagne
La villeCologne
période17/05/1620/05/16

Empreinte digitale

Aging of materials
Acoustic waves
Mathematical models

Citer ceci

Kobayashi, R., & Lambiotte, R. (2016). TiDeH: Time-dependent Hawkes process for predicting retweet dynamics. Dans Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016 (p. 191-200). AAAI Press.
Kobayashi, Ryota ; Lambiotte, Renaud. / TiDeH : Time-dependent Hawkes process for predicting retweet dynamics. Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016. AAAI Press, 2016. p. 191-200
@inproceedings{d618fcabf48d4e46a6566c89f9fc700b,
title = "TiDeH: Time-dependent Hawkes process for predicting retweet dynamics",
abstract = "Online social networking services allow their users to post content in the form of text, images or videos. The main mechanism driving content diffusion is the possibility for users to re-share the content posted by their social connections, which may then cascade across the system. A fundamental problem when studying information cascades is the possibility to develop sound mathematical models, whose parameters can be calibrated on empirical data, in order to predict the future course of a cascade after a window of observation. In this paper, we focus on Twitter and, in particular, on the temporal patterns of retweet activity for an original tweet. We model the system by Time-Dependent Hawkes process (TiDeH), which properly takes into account the circadian nature of the users and the aging of information. The input of the prediction model are observed retweet times and structural information about the underlying social network. We develop a procedure for parameter optimization and for predicting the future profiles of retweet activity at different time resolutions. We validate our methodology on a large corpus of Twitter data and demonstrate its systematic improvement over existing approaches in all the time regimes.",
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Kobayashi, R & Lambiotte, R 2016, TiDeH: Time-dependent Hawkes process for predicting retweet dynamics. Dans Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016. AAAI Press, p. 191-200, 10th International Conference on Web and Social Media, ICWSM 2016, Cologne, Allemagne, 17/05/16.

TiDeH : Time-dependent Hawkes process for predicting retweet dynamics. / Kobayashi, Ryota; Lambiotte, Renaud.

Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016. AAAI Press, 2016. p. 191-200.

Résultats de recherche: Contribution dans un livre/un catalogue/un rapport/dans les actes d'une conférenceArticle dans les actes d'une conférence/un colloque

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AU - Lambiotte, Renaud

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AB - Online social networking services allow their users to post content in the form of text, images or videos. The main mechanism driving content diffusion is the possibility for users to re-share the content posted by their social connections, which may then cascade across the system. A fundamental problem when studying information cascades is the possibility to develop sound mathematical models, whose parameters can be calibrated on empirical data, in order to predict the future course of a cascade after a window of observation. In this paper, we focus on Twitter and, in particular, on the temporal patterns of retweet activity for an original tweet. We model the system by Time-Dependent Hawkes process (TiDeH), which properly takes into account the circadian nature of the users and the aging of information. The input of the prediction model are observed retweet times and structural information about the underlying social network. We develop a procedure for parameter optimization and for predicting the future profiles of retweet activity at different time resolutions. We validate our methodology on a large corpus of Twitter data and demonstrate its systematic improvement over existing approaches in all the time regimes.

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Kobayashi R, Lambiotte R. TiDeH: Time-dependent Hawkes process for predicting retweet dynamics. Dans Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016. AAAI Press. 2016. p. 191-200