IDEAS home Printed from https://ideas.repec.org/a/igg/jiit00/v17y2021i2p1-11.html
   My bibliography  Save this article

Analysing Twitter Data for Phishing Tweets Identification

Author

Listed:
  • Falah Hassan Ali Al-Akashi

    (University of Kufa, Iraq)

Abstract

Detecting threats like adult, violent, and phishing tweets on online social networks is a crucial issue in recent years. The aim of the work is to identify phishing content from the users' perspective in real-time tweets. To outline such content comprehensively, lexicon analysis with sentiments are encapsulated to investigate tweets that yield phishing dynamic keywords, while some features and parameters are altered to optimize the performance. To support the preliminary study, the approach is rigorously designed to assemble users' opinions on completely different classes of phishing content. Each direct and indirect opinions as well as recently projected opinions are listed to characterize all sorts of phishing content. The authors use word level analysis with sentiments to build keyword blacklist lexicons. High promising results and high level of accuracy and performance are obtained experimentally if compared with the alternative algorithms.

Suggested Citation

  • Falah Hassan Ali Al-Akashi, 2021. "Analysing Twitter Data for Phishing Tweets Identification," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 17(2), pages 1-11, April.
    • Handle: RePEc:igg:jiit00:v:17:y:2021:i:2:p:1-11
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJIIT.2021040105
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Jason Q. & Craciun, Georgiana & Shin, Dongwoo, 2010. "When does electronic word-of-mouth matter? A study of consumer product reviews," Journal of Business Research, Elsevier, vol. 63(12), pages 1336-1341, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zou, Lili Wenli & Chan, Ricky Y.K., 2019. "Why and when do consumers perform green behaviors? An examination of regulatory focus and ethical ideology," Journal of Business Research, Elsevier, vol. 94(C), pages 113-127.
    2. Reema Nofal & Pelin Bayram & Okechukwu Lawrence Emeagwali & Lu’ay Al-Mu’ani, 2022. "The Effect of eWOM Source on Purchase Intention: The Moderation Role of Weak-Tie eWOM," Sustainability, MDPI, vol. 14(16), pages 1-20, August.
    3. Moradi, Masoud & Dass, Mayukh & Kumar, Piyush, 2023. "Differential effects of analytical versus emotional rhetorical style on review helpfulness," Journal of Business Research, Elsevier, vol. 154(C).
    4. Ricky Y. K. Chan, 2021. "Do chief information officers matter for sustainable development? Impact of their regulatory focus on green information technology strategies and corporate performance," Business Strategy and the Environment, Wiley Blackwell, vol. 30(5), pages 2523-2534, July.
    5. Raoofpanah, Iman & Zamudio, César & Groening, Christopher, 2023. "Review reader segmentation based on the heterogeneous impacts of review and reviewer attributes on review helpfulness: A study involving ZIP code data," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    6. Casaló, Luis V. & Flavián, Carlos & Guinalíu, Miguel & Ekinci, Yuksel, 2015. "Avoiding the dark side of positive online consumer reviews: Enhancing reviews' usefulness for high risk-averse travelers," Journal of Business Research, Elsevier, vol. 68(9), pages 1829-1835.
    7. Kim, Junyong & Gupta, Pranjal, 2012. "Emotional expressions in online user reviews: How they influence consumers' product evaluations," Journal of Business Research, Elsevier, vol. 65(7), pages 985-992.
    8. Alain Yee Loong Chong & Eugene Ch’ng & Martin J. Liu & Boying Li, 2017. "Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5142-5156, September.
    9. Bin Guo & Shasha Zhou, 2017. "What makes population perception of review helpfulness: an information processing perspective," Electronic Commerce Research, Springer, vol. 17(4), pages 585-608, December.
    10. Jason Zhang & Hong Zhu & Hung-bin Ding, 2013. "Board Composition and Corporate Social Responsibility: An Empirical Investigation in the Post Sarbanes-Oxley Era," Journal of Business Ethics, Springer, vol. 114(3), pages 381-392, May.
    11. Parsad, Chandan & Prashar, Sanjeev & Vijay, T. Sai & Kumar, Mukesh, 2021. "Do promotion and prevention focus influence impulse buying: The role of mood regulation, shopping values, and impulse buying tendency," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    12. Srivastava, Vartika & Kalro, Arti D., 2019. "Enhancing the Helpfulness of Online Consumer Reviews: The Role of Latent (Content) Factors," Journal of Interactive Marketing, Elsevier, vol. 48(C), pages 33-50.
    13. Kim, Jikyung (Jeanne) & Dong, Hang & Choi, Jeonghye & Chang, Sue Ryung, 2022. "Sentiment change and negative herding: Evidence from microblogging and news," Journal of Business Research, Elsevier, vol. 142(C), pages 364-376.
    14. Rong, Jia & Vu, Huy Quan & Law, Rob & Li, Gang, 2012. "A behavioral analysis of web sharers and browsers in Hong Kong using targeted association rule mining," Tourism Management, Elsevier, vol. 33(4), pages 731-740.
    15. Hernández-Ortega, Blanca, 2020. "When the performance comes into play: The influence of positive online consumer reviews on individuals' post-consumption responses," Journal of Business Research, Elsevier, vol. 113(C), pages 422-435.
    16. Juan Feng & Xin Li & Xiaoquan (Michael) Zhang, 2019. "Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence," Information Systems Research, INFORMS, vol. 30(4), pages 1107-1123, December.
    17. Herrmann, Andrea M. & Zaal, Petra M. & Chappin, Maryse M.H. & Schemmann, Brita & Lühmann, Amelie, 2023. "“We don't need no (higher) education” - How the gig economy challenges the education-income paradigm," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    18. France, Stephen L. & Shi, Yuying & Kazandjian, Brett, 2021. "Web Trends: A valuable tool for business research," Journal of Business Research, Elsevier, vol. 132(C), pages 666-679.
    19. Zhang, Hao & Liang, Xiaoning & Qi, Chenyue, 2021. "Investigating the impact of interpersonal closeness and social status on electronic word-of-mouth effectiveness," Journal of Business Research, Elsevier, vol. 130(C), pages 453-461.
    20. King, Robert Allen & Racherla, Pradeep & Bush, Victoria D., 2014. "What We Know and Don't Know About Online Word-of-Mouth: A Review and Synthesis of the Literature," Journal of Interactive Marketing, Elsevier, vol. 28(3), pages 167-183.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jiit00:v:17:y:2021:i:2:p:1-11. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.