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Using diffusion of innovation theory and sentiment analysis to analyze attitudes toward driving adoption by Saudi women

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  • Al-Razgan, Muna
  • Alrowily, Asma
  • Al-Matham, Rawan N.
  • Alghamdi, Khulood M.
  • Shaabi, Maha
  • Alssum, Lama

Abstract

Although several studies have used sentiment analysis to examine social media content, relatively few have complemented this work with sociological theories. This study employed the diffusion of innovation (DOI) framework to provide a deeper understanding of the recent debate on whether women in Saudi Arabia should be granted the right to drive. The outlook of proponents and opponents was considered by using detailed Arabic Twitter data. The sentiment analysis approach was used. The findings were analyzed on the basis of DOI stages, and the innovation–decision process demonstrated that 60% of Twitter users supported the governments' approval of women's right to drive and 40% either opposed the order or had a neutral opinion. The finding of our analysis suggests that Saudi society corresponds the DOI stages and exhibits the tendency to support the right of women to drive. This study contributes to DOI research, particularly concerning the use of social media for studying opinions on important unsettled social matters.

Suggested Citation

  • Al-Razgan, Muna & Alrowily, Asma & Al-Matham, Rawan N. & Alghamdi, Khulood M. & Shaabi, Maha & Alssum, Lama, 2021. "Using diffusion of innovation theory and sentiment analysis to analyze attitudes toward driving adoption by Saudi women," Technology in Society, Elsevier, vol. 65(C).
    • Handle: RePEc:eee:teinso:v:65:y:2021:i:c:s0160791x21000336
    DOI: 10.1016/j.techsoc.2021.101558
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    References listed on IDEAS

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    1. Lama Altoaimy, 2018. "Driving Change on Twitter: A Corpus-Assisted Discourse Analysis of the Twitter Debates on the Saudi Ban on Women Driving," Social Sciences, MDPI, vol. 7(5), pages 1-14, May.
    2. Samargandi, Nahla & Al Mamun, Md & Sohag, Kazi & Alandejani, Maha, 2019. "Women at work in Saudi Arabia: Impact of ICT diffusion and financial development," Technology in Society, Elsevier, vol. 59(C).
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    4. Afnan MuhammadSalh AlSukhayri & Muhammad Ahtisham Aslam & Kawther Saeedi & Muhamad Sheraz Arshed Malik, 2020. "A Linked Open Data-Oriented Sustainable System for Transparency and Open Access to Government Data: A Case Study of the Public’s Response to Women’s Driving in Saudi Arabia," Sustainability, MDPI, vol. 12(20), pages 1-26, October.
    5. Rehab M. Duwairi & Islam Qarqaz, 2016. "A framework for Arabic sentiment analysis using supervised classification," International Journal of Data Mining, Modelling and Management, Inderscience Enterprises Ltd, vol. 8(4), pages 369-381.
    6. Luppicini, Rocci & Saleh, Ramzia H., 2017. "The role of online social networks for divorced Saudi women in the face of social, psychological, economic, and legal challenges," Technology in Society, Elsevier, vol. 51(C), pages 142-152.
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    Cited by:

    1. Nouf Al-Shenaifi & Aqil M. Azmi & Manar Hosny, 2024. "Advancing AI-Driven Linguistic Analysis: Developing and Annotating Comprehensive Arabic Dialect Corpora for Gulf Countries and Saudi Arabia," Mathematics, MDPI, vol. 12(19), pages 1-18, October.
    2. Santoveña-Casal, Sonia & Pérez, Ma Dolores Fernández, 2022. "Relevance of E-Participation in the state health campaign in Spain: #EstoNoEsUnJuego / #ThisIsNotAGame," Technology in Society, Elsevier, vol. 68(C).
    3. Xu, Yong & Yuan, Ling & Khalfaoui, Rabeh & Radulescu, Magdalena & Mallek, Sabrine & Zhao, Xin, 2023. "Making technological innovation greener: Does firm digital transformation work?," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    4. Hanan S. AlEssa & Christopher M. Durugbo, 2022. "Understanding innovative work behaviour of women in service firms," Service Business, Springer;Pan-Pacific Business Association, vol. 16(4), pages 825-862, December.
    5. Singh, Yashdeep & Suri, Pradeep Kumar, 2022. "An empirical analysis of mobile learning app usage experience," Technology in Society, Elsevier, vol. 68(C).
    6. Xing, Yunfei & Wang, Xiwei & Qiu, Chengcheng & Li, Yueqi & He, Wu, 2022. "Research on opinion polarization by big data analytics capabilities in online social networks," Technology in Society, Elsevier, vol. 68(C).
    7. Malik, Aqdas & Berggren, Walter & Al-Busaidi, Adil S., 2022. "Instagram as a research tool for examining tobacco-related content: A methodological review," Technology in Society, Elsevier, vol. 70(C).

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