Toward efficient and effective bullying detection in online social network
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Toward efficient and effective bullying detection in online social network Jiale Wu1 · Mi Wen1 · Rongxing Lu2 · Beibei Li3 · Jinguo Li1 Received: 15 August 2019 / Accepted: 28 September 2019 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract With the advances of Information Communication Technology (ICT) and the popularity of intelligent terminals, Online Social Network, which is characterized by powerful functions of information publishing, dissemination, acquisition and sharing, has attracted a huge number of users and become one of the most popular internet application services currently. However, the growth of Online Social Network has also led to the emergence of cyberbullying issues. Information spreads extremely fast via Online Social Network, making the harm caused by cyberbullying grow exponentially with time. As a result, it becomes critical to detect the cyberbullying in a quick and efficient way. In this paper, in order to solve this challenge, we propose an improved TF-IDF based fastText (ITFT) model for effective cyberbullying detection. Specifically, in our proposed scheme, we improve the TF-IDF algorithm by adding the position weight, keywords are extracted by the improved algorithm and used as input to achieve the purpose of filtering noise data to improve the accuracy. We use the fastText to construct a binary classifier to categorize the input data. Extensive experiments are conducted, and the results demonstrate that our proposed scheme can achieve better efficiency and accuracy in cyberbullying detection as compared with baselines. Keywords Cyberbullying detection · Online social network · Text classification · Natural language processing
1 Introduction This work is supported by the National Natural Science Foundation of China under Grant No.61872230, No.61702321 and No.61572311 Mi Wen
[email protected] Jiale Wu [email protected] Rongxing Lu [email protected] Beibei Li [email protected] Jinguo Li [email protected] 1
College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai, 200090, China
2
Faculty of Computer Science, University of New Brunswick, Fredericton, E3B 5A3, Canada
3
College of Cybersecurity, Sichuan University, Chengdu, 610065, China
With the advances of internet and information communication tools, a new form of bullying has emerged in Online Social Network, named cyberbullying [1]. Essentially, cyberbullying refers to the use of information and communication technologies such as email, instant text messages, personal websites or online personal voting sites to intentionally and repeatedly commit malicious acts aimed at harming others. The harm caused by the phenomenon of cyberbullying has gradually attracted the attention of the society, and an increasing number of researchers have put their efforts in the research of cyberbullying [2]. Compared with traditional bullying, cyberbullying may be more harmful. This is due to cyberbullying uses the Online Social Network as the medium and spreads faster in a larger scale, as
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