Big data analytics and international negotiations: Sentiment analysis of Brexit negotiating outcomes. (April 2020)

• Record Type: Journal Article
• Authors: Georgiadou, Elena; Angelopoulos, Spyros; Drake, Helen
• Is Part Of: International journal of information management. Volume 51(2020)
• Publication Date: 2020-04
• Subjects: Big data analytics -- Sentiment analysis -- International negotiations -- Brexit -- Decision making -- Policy making; Social sciences -- Information services -- Periodicals; Social sciences -- Research -- Periodicals; Information science -- Periodicals; Management information systems -- Periodicals; Knowledge management -- Periodicals; Sciences sociales -- Documentation, Services de -- Périodiques; Sciences sociales -- Recherche -- Périodiques; Sciences de l'information -- Périodiques; Systèmes d'information de gestion -- Périodiques; Information science; Management information systems; Social sciences -- Information services; Social sciences -- Research; Periodicals; Electronic journals; 025.52068
• DOI: 10.1016/j.ijinfomgt.2019.102048
• Languages: English
• ISSNs: 0268-4012

Abstract

Highlights: Twitter has potential as a real-time barometer of public sentiment towards international negotiating outcomes. SA can operationalise and decipher collective preferences to inform decision making in negotiations. Applied to Brexit positive emotion is associated with 'soft' types of Brexit. Applied to Brexit negative emotion is associated with 'hard' types of Brexit and 'no deal' Abstract: We introduce Big Data Analytics (BDA) and Sentiment Analysis (SA) to the study of international negotiations, through an application to the case of the UK-EU Brexit negotiations and the use of Twitter user sentiment. We show that SA of tweets has potential as a real-time barometer of public sentiment towards negotiating outcomes to inform government decision-making. Despite the increasing need for information on collective preferences regarding possible negotiating outcomes, negotiators have been slow to capitalise on BDA. Through SA on a corpus of 13, 018, 367 tweets on defined Brexit hashtags, we illustrate how SA can provide a platform for decision-makers engaged in international negotiations to grasp collective preferences. We show that BDA and SA can enhance decision-making and strategy in public policy and negotiation contexts of the magnitude of Brexit. Our findings indicate that the preferred or least preferred Brexit outcomes could have been inferred by the emotions expressed by Twitter users. We argue that BDA can be a mechanism to map the different options available to decision-makers and bring insights to and inform their decision-making. Our work, thereby, proposes SA as part of the international negotiation toolbox to remedy for the existing informational gap between decision makers and citizens' preferred outcomes.