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In Quest of Significance: Identifying Types of Twitter Sentiment Events that Predict Spikes in Sales

Kolchyna, O; Souza, TTP; Aste, T; Treleaven, PC; (2015) In Quest of Significance: Identifying Types of Twitter Sentiment Events that Predict Spikes in Sales. Cornell University Library: Ithaca, NY, USA. Green open access

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Abstract

We study the power of Twitter events to predict consumer sales events by analysing sales for 75 companies from the retail sector and over 150 million tweets mentioning those companies along with their sentiment. We suggest an approach for events identification on Twitter extending existing methodologies of event study. We also propose a robust method for clustering Twitter events into different types based on their shape, which captures the varying dynamics of information propagation through the social network. We provide empirical evidence that through events differentiation based on their shape we can clearly identify types of Twitter events that have a more significant power to predict spikes in sales than the aggregated Twitter signal.

Type: Working / discussion paper
Title: In Quest of Significance: Identifying Types of Twitter Sentiment Events that Predict Spikes in Sales
Open access status: An open access version is available from UCL Discovery
Publisher version: https://arxiv.org/abs/1508.03981
Language: English
Keywords: Sentiment analysis, social media, Twitter, sales forecasting, clustering, spikes, events detection, event study
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10043057
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