Research Article
Sentiment Analysis of Opinions over Time Toward Saudi Women’s Sports
@INPROCEEDINGS{10.1007/978-3-031-18123-8_19, author={Norah J. Almateg and Sarah M. BinQasim and Jawaher N. Alshahrani and Ahad Y. Marghalani and Zahyah H. Alharbi}, title={Sentiment Analysis of Opinions over Time Toward Saudi Women’s Sports}, proceedings={Multimedia Technology and Enhanced Learning. 4th EAI International Conference, ICMTEL 2022, Virtual Event, April 15-16, 2022, Proceedings}, proceedings_a={ICMTEL}, year={2022}, month={10}, keywords={Women’s sport Sentiment analysis Natural Language Processing (NLP)}, doi={10.1007/978-3-031-18123-8_19} }- Norah J. Almateg
Sarah M. BinQasim
Jawaher N. Alshahrani
Ahad Y. Marghalani
Zahyah H. Alharbi
Year: 2022
Sentiment Analysis of Opinions over Time Toward Saudi Women’s Sports
ICMTEL
Springer
DOI: 10.1007/978-3-031-18123-8_19
Abstract
The examining and promoting women’s health is essential to the general well-being of society. As sports activities are important for maintaining physical, psychological, and social health, female participation in sports is one of the significant factors in achieving the goals of Saudi Arabia’s Vision 2030. In this paper, sentiment analysis was used to compare the society opinions pre and post permit-ting Saudi women’s sports, between 2017 and 2021. To identify the sentiment of a given tweet, a lexicon for the Saudi dialect was developed. In total, 12,000 tweets were collected and prepared. After data preparation, the tweets were reduced to 1,999 across all selected hashtags for this the initial study. We used four different hashtags related to Saudi women’s sports, namely, (#Officiallyfemalesportsinschools) represented as a Pre-Hashtag, whereas (#WomenSport) and (#FemaleSport) as Pre and Post Hashtags, and (#Tahani _Alqahtani) as Post-Hashtag. The data in each hashtag were classified as positive, negative, or neutral. To build the sentiment classifier model, A Support Vector Machine (SVM) classifier was applied. The highest average accuracy was for the Pre-Hashtag with a score of 91%, followed by the Pre and Post Hashtag with a score of 85%. Finally, the Post Hashtag has the lowest score of 72%. The results show that 81% of the sample are positive. Accordingly, women have been becoming more motivated to engage in sports participation, as well as Saudi society is being more encouraging.
