Big data analytics and international negotiations: Sentiment analysis of Brexit negotiating outcomes

被引:51
|
作者
Georgiadou, Elena [1 ]
Angelopoulos, Spyros [2 ]
Drake, Helen [3 ]
机构
[1] Loughborough Univ, Sch Business & Econ, Loughborough, Leics, England
[2] Tilburg Univ, Tilburg Sch Econ & Management, Tilburg, Netherlands
[3] Loughborough Univ London, London, England
关键词
Big data analytics; Sentiment analysis; International negotiations; Brexit; Decision making; Policy making; SOCIAL MEDIA; DOMESTIC POLITICS; TWITTER; EMOTIONS; DECISION; SCIENCE; DIPLOMACY; PARADIGM; OPINION; TOPICS;
D O I
10.1016/j.ijinfomgt.2019.102048
中图分类号
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号
1205 ; 120501 ;
摘要
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.
引用
收藏
页数:9
相关论文
共 50 条
  • [1] Big data analytics for disaster response and recovery through sentiment analysis
    Ragini, J. Rexiline
    Anand, P. M. Rubesh
    Bhaskar, Vidhyacharan
    [J]. INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2018, 42 : 13 - 24
  • [2] HARNESSING INVESTOR SENTIMENT USING BIG DATA ANALYTICS
    Johnman, Mark
    Gepp, Adrian
    Vanstone, Bruce
    [J]. JASSA-THE FINSIA JOURNAL OF APPLIED FINANCE, 2019, (03): : 4 - 8
  • [3] EDUCATIONAL BIG DATA ANALYTICS USING SENTIMENT ANALYSIS FOR STUDENT REQUIREMENT ANALYSIS ON COURSES
    Wang, Meida
    Yang, Qingfeng
    [J]. SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2024, 25 (05): : 3858 - 3866
  • [4] Survey on Sentiment Analysis based Stock Prediction using Big data Analytics
    Balaji, S. Naveen
    Paul, P. Victer
    Saravanan, R.
    [J]. 2017 INNOVATIONS IN POWER AND ADVANCED COMPUTING TECHNOLOGIES (I-PACT), 2017,
  • [5] Big Data Analytics and Deep Learning Based Sentiment Analysis System for Sales Prediction
    Khatiwada, Aamod
    Kadariya, Pradeep
    Agrahari, Sandip
    Dhakal, Rabin
    [J]. 2019 IEEE PUNE SECTION INTERNATIONAL CONFERENCE (PUNECON), 2019,
  • [6] Census Big Data Analytics Use: International Cross Case Analysis
    Chatfield, Akemi Takeoka
    Ojo, Adegboyega
    Puron-Cid, Gabriel
    Reddick, Christopher G.
    [J]. PROCEEDINGS OF THE 19TH ANNUAL INTERNATIONAL CONFERENCE ON DIGITAL GOVERNMENT RESEARCH (DGO 2018): GOVERNANCE IN THE DATA AGE, 2018, : 74 - 83
  • [7] Making sense of consumers' tweets Sentiment outcomes for fast fashion retailers through Big Data analytics
    Pantano, Eleonora
    Giglio, Simona
    Dennis, Charles
    [J]. INTERNATIONAL JOURNAL OF RETAIL & DISTRIBUTION MANAGEMENT, 2019, 47 (09) : 915 - 927
  • [8] An Intelligent Cognitive-Inspired Computing with Big Data Analytics Framework for Sentiment Analysis and Classification
    Jain, Deepak Kumar
    Boyapati, Prasanthi
    Venkatesh, J.
    Prakash, M.
    [J]. INFORMATION PROCESSING & MANAGEMENT, 2022, 59 (01)
  • [9] SENTIMENT ANALYSIS USING BIG DATA
    Ramanujam, R. Suresh
    Nancyamala, R.
    Nivedha, J.
    Kokila, J.
    [J]. 2015 INTERNATIONAL CONFERENCE ON COMPUTATION OF POWER, ENERGY, INFORMATION AND COMMUNICATION (ICCPEIC), 2015, : 480 - 484
  • [10] Improving VLBW infant outcomes with big data analytics
    F. Sessions Cole
    [J]. Pediatric Research, 2021, 90 : 20 - 21