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The Wisdom of the Silent Crowd: Predicting the Match Results of World Cup 2018 through Twitter

by Abdullah Talha Kabakus, Mehmet Simsek, Ibrahim Belenli
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 27
Year of Publication: 2018
Authors: Abdullah Talha Kabakus, Mehmet Simsek, Ibrahim Belenli
10.5120/ijca2018918125

Abdullah Talha Kabakus, Mehmet Simsek, Ibrahim Belenli . The Wisdom of the Silent Crowd: Predicting the Match Results of World Cup 2018 through Twitter. International Journal of Computer Applications. 182, 27 ( Nov 2018), 40-45. DOI=10.5120/ijca2018918125

@article{ 10.5120/ijca2018918125,
author = { Abdullah Talha Kabakus, Mehmet Simsek, Ibrahim Belenli },
title = { The Wisdom of the Silent Crowd: Predicting the Match Results of World Cup 2018 through Twitter },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2018 },
volume = { 182 },
number = { 27 },
month = { Nov },
year = { 2018 },
issn = { 0975-8887 },
pages = { 40-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number27/30151-2018918125/ },
doi = { 10.5120/ijca2018918125 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:12:40.111552+05:30
%A Abdullah Talha Kabakus
%A Mehmet Simsek
%A Ibrahim Belenli
%T The Wisdom of the Silent Crowd: Predicting the Match Results of World Cup 2018 through Twitter
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 27
%P 40-45
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Social networks have attracted much attention thanks to their availability, being the source of information in almost everything related to life, and giving the chance for users to discover the things and people related to them. Global and highly popular events such as the FIFA World Cup are always welcomed by social networking sites. Furthermore, these social networking sites customize themselves and provide some specific content for this global events. From this point of view, we have collected 38,371,358 tweets during the FIFA World Cup 2018 which were posted by 7,876,519 unique Twitter users. The aim of this study is proposing a prediction system that evaluates the teams who qualified for the FIFA World Cup 2018 through their squad, and their performances in the early stages of the competition in order to predict the match results of the further stages. For this reason, a number of different types of machine learning algorithms are utilized after building a machine learning model which is based on novel features. According to the experimental results, the best accuracy of the proposed system for the match result prediction is calculated as high as 87.5% which is quite better than the related work. The experimental results demonstrate the effectiveness of social network based features.

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Index Terms

Computer Science
Information Sciences

Keywords

Machine Learning Sports Result Prediction Social Network Analysis Twitter FIFA World Cup.

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