10,508 research outputs found
A Socio-Informatic Approach to Automated Account Classification on Social Media
Automated accounts on social media have become increasingly problematic. We
propose a key feature in combination with existing methods to improve machine
learning algorithms for bot detection. We successfully improve classification
performance through including the proposed feature.Comment: International Conference on Social Media and Societ
A Dynamical Model of Twitter Activity Profiles
The advent of the era of Big Data has allowed many researchers to dig into
various socio-technical systems, including social media platforms. In
particular, these systems have provided them with certain verifiable means to
look into certain aspects of human behavior. In this work, we are specifically
interested in the behavior of individuals on social media platforms---how they
handle the information they get, and how they share it. We look into Twitter to
understand the dynamics behind the users' posting activities---tweets and
retweets---zooming in on topics that peaked in popularity. Three mechanisms are
considered: endogenous stimuli, exogenous stimuli, and a mechanism that
dictates the decay of interest of the population in a topic. We propose a model
involving two parameters and describing the tweeting
behaviour of users, which allow us to reconstruct the findings of Lehmann et
al. (2012) on the temporal profiles of popular Twitter hashtags. With this
model, we are able to accurately reproduce the temporal profile of user
engagements on Twitter. Furthermore, we introduce an alternative in classifying
the collective activities on the socio-technical system based on the model.Comment: 10 pages, 5 figure
Elite Tweets: Analysing the Twitter Communication Patterns of Labour Party Peers in the House of Lords
The micro-blogging platform Twitter has gained notoriety for its status as both a communication channel between private individuals, and as a public forum monitored by journalists, the public, and the state. Its potential application for political communication has not gone unnoticed; politicians have used Twitter to attract voters, interact with constituencies and advance issue-based campaigns. This article reports on the preliminary results of the research teamâs work with 21 peers sitting on the Labour frontbench. It is based on the monitoring and archival of the peersâ activity on Twitter for a period of 100 days from 16th May to 28th September 2012. Using a sample of more than 4,363 tweets and a mixed methodology combining semantic analysis, social network analysis and quantitative analysis, this paper explores the peersâ patterns of usage and communication on Twitter. Key findings are that as a tweeting community their behavior is consistent with others, however there is evidence that a coherent strategy is lacking. Labour peers tend to work in ego networks of self-interest as opposed to working together to promote party polic
Modeling trend progression through an extension of the Polya Urn Process
Knowing how and when trends are formed is a frequently visited research goal.
In our work, we focus on the progression of trends through (social) networks.
We use a random graph (RG) model to mimic the progression of a trend through
the network. The context of the trend is not included in our model. We show
that every state of the RG model maps to a state of the Polya process. We find
that the limit of the component size distribution of the RG model shows
power-law behaviour. These results are also supported by simulations.Comment: 11 pages, 2 figures, NetSci-X Conference, Wroclaw, Poland, 11-13
January 2016. arXiv admin note: text overlap with arXiv:1502.0016
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