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The Department of Computer Science at the University of Cyprus cordially invites you to the Presentation entitled:

Analysis of Evolution, Dynamics and Vulnerabilities of Twitter

Speaker: Mrs. Despoina Antonakaki
Affiliation: University of Cyprus, Cyprus
Category: Presentation
Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions)
Date: Monday, October 5, 2015
Time: 15:00-16:00 EET
Host: George Pallis (gpallis-AT-cs.ucy.ac.cy)
URL: https://www.cs.ucy.ac.cy/colloquium/presentations.php#cs.ucy.pres.2015.antonakaki

Abstract:
Twitter is a popular microblogging social platform, established on 2006 and as of today has reached 645 million registered users where half of them are monthly active. Except from ordinary individual users, Twitter is utilized from news agents, public figures, and organizations to disseminate their activity and engage in discussion with other users. The research community has focused several studies on Twitter, covering a wide spectrum of experiments. The first study we conducted was focused on the exploitation of trending topics towards spam dissemination. We analyzed a large collection of tweets and explore the dynamics of popular trends and other Twitter features in regards to deliberate misuse. We identified a specific class of trend-exploiting campaigns that exhibits a stealthy behavior and hides spam URLs within Google search-result links. We build a spam classifier for both users and tweets, and demonstrate its simplicity and efficiency. Finally, we visualize these spam campaigns and reveal their inner structure. [Antonakaki et al, SocInfo 2014] Our second study was focused on the analysis of the social graph of Twitter. The online activity and the dynamics of the social graph of Twitter are considered to be indicative of the tendencies of the off-line social life and reflect the preferences of the public in general [Java A. et al, WebKDD/SNA-KDD '07]. We propose a sampling framework that allows the estimation of graph properties on large social networks. We apply this framework to a subset of Twitter’s social network that has 13.2 million users, 8.3 billion edges and covers the complete Twitter timeline (from April 2006 to January 2015). We derive estimation on the time evolution of 24 graph properties many of which have never been measured on large social networks. We further discuss how these estimations shed more light on the inner structure and growth dynamics of Twitter’s social network.

Short Bio:
Despoina Antonakaki finished her Bachelor at the Computer Science Department of the University of Crete. She obtained her MSc in Biomedical Computing & Technology at the University of Crete & BMI of ICS -FORTH at Heraklion, Greece on April 2006. On September 2006 till December 2009 she worked on Software design and development at the Centre of Communications & Networking of the University of Crete. Specifically her main focus included design, development and support of video streaming services (video on demand and webcast applications). She also worked on the development, support and administration of networking application related with LDAP, helpdesk, directory, telephone accounting. On February 2010 till September 2013 Despoina worked as a software engineer in the Genomics Coordination Centre of the Genetics department of University of Groningen, UMCG in the Netherlands. Mainly she focused on Java software development for MOLGENIS framework for life science research, data indexing, search engine optimization and Semantic Integration. She was also the leader software developer for the Catalogue of Dutch Biobanks for BBMRI-NL & Biobank variable catalogue for Lifelines. She focused also on web services development for OntoCAT, which was highly accessed, published on BMC Bioinformatics 2011. Currently she is a PhD fellow for ISocial ITN program and my main focus is on analysis, dynamics and vulnerabilities of OSNs.

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