Towards understanding cyberbullying behavior in a semi-anonymous social network

  title={Towards understanding cyberbullying behavior in a semi-anonymous social network},
  author={Homa Hosseinmardi and Richard O. Han and Qin Lv and Shivakant Mishra and Amir Ghasemianlangroodi},
  journal={2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)},
Cyberbullying has emerged as an important and growing social problem, wherein people use online social networks and mobile phones to bully victims with offensive text, images, audio and video on a 24/7 basis. This paper studies negative user behavior in the social network, a popular new site that has led to many cases of cyberbullying, some leading to suicidal behavior.We examine the occurrence of negative words in's question+answer profiles along with the social network of “likes… 
Analyzing Labeled Cyberbullying Incidents on the Instagram Social Network
This work collected a sample data set consisting of Instagram images and their associated comments and employed human contributors at the crowd-sourced CrowdFlower website to label these media sessions for cyberbullying incidents.
Mining Patterns of Cyberbullying on Twitter
A detailed analysis of a large–scale real–world dataset is performed to identify online social network topology structure features that are the most prominent in enhancing the accuracy of state–of–the–art classification methods for cyberbullying detection.
A Comparison of Common Users across Instagram and to Better Understand Cyberbullying
An analysis of the negativity and positivity of word usage in posts by common users of these two social networks is performed and the relationship between anonymity and negativity is further explored.
Cyberbullying Social Role Detection on Instagram
A social role detection framework is proposed to understand cyberbullying on Instagram and a dataset that contains users’ records on Instagram is selected as a case study and refined by constructing a victim-bully-supporter network on Instagram.
Understanding Cyberbullying on Instagram and via Social Role Detection
This work proposes a social role detection framework to understand cyberbullying on online social platforms, and selects a dataset that contains users’ records on both Instagram and as a case study.
A Framework for Cyberbullying Detection in Social Network
A framework deployed for the detecting negative online interactions in terms of abusive contents carried out through text messages as well as images is proposed and the combination of text & image analysis techniques is considered as a suitable platform for the detection of potential cyber bullying threats.
Detecting Cyberbullying and Cyberaggression in Social Media
This work presents a robust methodology to distinguish bullies and aggressors from normal Twitter users by considering text, user, and network-based attributes, and discusses the current status of Twitter user accounts marked as abusive by the methodology and the performance of potential mechanisms that can be used by Twitter to suspend users in the future.
Beyond Cyberbullying: Self-Disclosure, Harm and Social Support on ASKfm
How the affordances specific to platforms like ASKfm might enable users to respond to cyberbullying in novel ways, engage in positive forms of self-disclosure, and gain social support on sensitive topics is discussed.
Careful what you share in six seconds: Detecting cyberbullying instances in Vine
This research paper investigates cyberbullying behaviors in Vine, a mobile based video-sharing online social network, and design novel approaches to automatically detect instances of cyberbullies over Vine media sessions.
Cyberbullying Identification Using Participant-Vocabulary Consistency
This study proposes a model that simultaneously discovers instigators and victims of bullying as well as new bullying vocabulary by starting with a corpus of social interactions and a seed dictionary of bullying indicators and formulate an objective function based on participant-vocabulary consistency.


Improved cyberbullying detection using gender information
It is demonstrated that taking gender-specific language features into account improves the discrimination capacity of a classifier to detect cyberbullying.
Common Sense Reasoning for Detection, Prevention, and Mitigation of Cyberbullying
An “air traffic control”-like dashboard is proposed, which alerts moderators to large-scale outbreaks that appear to be escalating or spreading and helps them prioritize the current deluge of user complaints.
Defining Cyberbullying: A Qualitative Research into the Perceptions of Youngsters
Data from 53 focus groups, which involved students from 10 to 18 years old, show that youngsters often interpret "cyberbullying" as "Internet bullying" and associate the phenomenon with a wide range
Cyberbullying definition and measurement: Some critical considerations
This definition implies that cyberbullying is similar to traditional bullying, but involving the use of new communication technologies. Its hostile trait derives from the aggressive nature of the
A Large-Scale Study of MySpace: Observations and Implications for Online Social Networks
An extensive analysis of over 1.9 million MySpace profiles helps to understand who is using these networks and how they are being used and finds a number of surprising results.
Measurement and analysis of online social networks
This paper examines data gathered from four popular online social networks: Flickr, YouTube, LiveJournal, and Orkut, and reports that the indegree of user nodes tends to match the outdegree; the networks contain a densely connected core of high-degree nodes; and that this core links small groups of strongly clustered, low-degree node at the fringes of the network.
Beyond Social Graphs: User Interactions in Online Social Networks and their Implications
This article proposes the use of “interaction graphs” to impart meaning to online social links by quantifying user interactions, and analyzes interaction graphs derived from Facebook user traces to validate several well-known social-based applications that rely on graph properties to infuse new functionality into Internet applications.
Students' perspectives on cyber bullying.
What is Twitter, a social network or a news media?
This work is the first quantitative study on the entire Twittersphere and information diffusion on it and finds a non-power-law follower distribution, a short effective diameter, and low reciprocity, which all mark a deviation from known characteristics of human social networks.
Networks: An Introduction
This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas.