Exploring characteristics of suspended users and network stability on Twitter

@article{Wei2016ExploringCO,
  title={Exploring characteristics of suspended users and network stability on Twitter},
  author={Wei Wei and Kenneth Joseph and Huan Liu and Kathleen M. Carley},
  journal={Social Network Analysis and Mining},
  year={2016},
  volume={6},
  pages={1-18}
}
Social media is rapidly becoming a medium of choice for understanding the cultural pulse of a region; e.g. for identifying what the population is concerned with and what kind of help is needed in a crisis. To assess this cultural pulse, it is critical to have an accurate assessment of who is saying what. Unfortunately, social media is also the home of users who engage in disruptive, disingenuous, and potentially illegal activity. A range of users, both human and non-human, carry out such social… Expand
Analyst as data scientist: surfing vs drowning in the information environment
Today’s analysts must process increasing amounts of information, including “Twitter-INT” 1 (social information such as Facebook, You-Tube videos, blogs, Twitter), as well as discern threat signaturesExpand
The Role of Suspended Accounts in Political Discussion on Social Media: Analysis of the 2017 French, UK and German Elections
Content moderation on social media is at the center of public and academic debate. In this study, we advance our understanding on which type of election-related content gets suspended by social mediaExpand
Efficient Representation of Interaction Patterns with Hyperbolic Hierarchical Clustering for Classification of Users on Twitter
TLDR
A feature extraction framework which compactly captures potentially insidious interaction patterns on Twitter and uses Hyperbolic Hierarchical Clustering (HypHC) which represents the features in the hyperbolic manifold to further separate communities amongst the users that work to boost the content of particular accounts. Expand
Use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey
TLDR
Results showed that flagging tweets lowered participants’ attitudes about them, though this effect was less pronounced in participants who frequently used social media or consumed more news, especially from Facebook or Fox News, suggesting that social media companies can flag suspicious or inaccurate content as a way to fight misinformation. Expand
Methods for defining dynamic online communities and community detection in fast-paced social media streams
TLDR
It is demonstrated in this work that standard community detection algorithms are challenged by the fast-paced dynamics and link sparsity of microblogging data, and it is argued that temporal characteristics must be considered for community detection methods in microblogting. Expand
Analyzing Polemics Evolution from Twitter Streams Using Author-based Social Networks
TLDR
This article conducts a time-related social network analysis of the evolution of the actor interactions, using time-series built from a total of 33 graph theory metrics, and allows for validated techniques on a complex dataset of 284 millions of tweets. Expand
Understanding cannabis information on social media: Examining tweets from verified, regular, and suspended users
TLDR
The findings from this study could be used to design public health education programs targeting young adults and adolescents and suggest that researchers employ both qualitative and quantitative methods to fully discern the subtle differences in health-related social media discussions. Expand
ORA: A Toolkit for Dynamic Network Analysis and Visualization
TLDR
ORA is a full function network analytics package that supports the user in creating, importing, exporting, manipulating, editing, analysing, comparing, contrasting, and forecasting changes in one or more networks. Expand
Leveraging Phone Numbers for Spam detection in Online Social Networks
Online Social Networks (OSNs) are platforms that have gained immense traction from society today. Social media has reshaped our social world and has been playing a pivotal role in sculpting ourExpand
Spam Diffusion in Social Networking Media using Latent Dirichlet Allocation
  • Poonam Tanwar
  • International Journal of Innovative Technology and Exploring Engineering
  • 2019
Like web spam has been a major threat to almost every aspect of the current World Wide Web, similarly social spam especially in information diffusion has led a serious threat to the utilities ofExpand
...
1
2
3
...

References

SHOWING 1-10 OF 63 REFERENCES
The fragility of Twitter social networks against suspended users
TLDR
Experimental results demonstrate that Twitter-based network structures and content are unstable, and can be highly impacted by the removal of suspended users, and exhibit regional and temporal variation that may be related to the political situation or civil unrest. Expand
Suspended accounts in retrospect: an analysis of twitter spam
TLDR
This study examines the abuse of online social networks at the hands of spammers through the lens of the tools, techniques, and support infrastructure they rely upon and identifies an emerging marketplace of illegitimate programs operated by spammers. Expand
Culture, Networks, Twitter and foursquare: Testing a Model of Cultural Conversion with Social Media Data
TLDR
This work uses Twitter data to extract the ego networks of individuals and foursquare check-ins to understand their cultural preferences, and validates one such model of the conversion of cultural capital to network position. Expand
Discovering geographical topics in the twitter stream
TLDR
An algorithm is presented by modeling diversity in tweets based on topical diversity, geographical diversity, and an interest distribution of the user by exploiting sparse factorial coding of the attributes, thus allowing it to deal with a large and diverse set of covariates efficiently. Expand
Empirical study of topic modeling in Twitter
TLDR
It is shown that by training a topic model on aggregated messages the authors can obtain a higher quality of learned model which results in significantly better performance in two real-world classification problems. Expand
On the precision of social and information networks
TLDR
This paper proves that the Kronecker-graph based generative model of Leskovec et al. satisfies an appropriate and natural definition of user interests, and shows that this model also has high precision, high recall, and low diameter. Expand
Detecting and Tracking Political Abuse in Social Media
TLDR
A machine learning framework that combines topological, content-based and crowdsourced features of information diffusion networks on Twitter to detect the early stages of viral spreading of political misinformation. Expand
A Bayesian Graphical Model to Discover Latent Events from Twitter
TLDR
A probabilistic graphical model is used to discover events within the data in a way that informs us of their spatial, temporal and topical focus and can be used to predict the location and time of texts that do not have these pieces of information, which accounts for much of the data on the web. Expand
On the Interplay between Social and Topical Structure
TLDR
The interface of two decisive structures forming the backbone of online social media is examined: the graph structure of social networks - who connects with whom - and the set structure of topical affiliations - who is interested in what, and computationally simple structural determinants can provide remarkable performance in both tasks. Expand
Embassies burning: toward a near-real-time assessment of social media using geo-temporal dynamic network analytics
TLDR
A rapid ethnographic approach for extracting information from Twitter and news media and then assessing that information using dynamic network analysis techniques is described to provide an integrated approach to assessing large dynamic networks. Expand
...
1
2
3
4
5
...