About Me

I am a PhD Student in the Computer Science Department at the University of Georgia, Athens, GA. I have been conducting my research studies under the supervision of Dr. I. Budak Arpinar.

Education

Before I joined the University of Georgia in 2012 for PhD program in Computer Science, I received my Masters of Engineering degree from the Department of Computer Engineering of Stevens Institute of Technology, Hoboken, NJ in 2011 and Bachelor's degree from the Department of Electronics Engineering of Ankara University, Ankara, Turkey, in 2006.

Research Interests

My research interests span several fields from computer science to social science forming an interdisciplinary field in between. I am particularly interested in; from a computer science perspective, "Social Computing", and from a social science perspective, "Computational Social Science", which will play a key role in processing and analyzing social data, especially after recent dramatic increase in the production of user-generated content. As it is considered to have a potential that can widen up the limits of information flow and provide a broader spectrum of reliable insights on social and political events, it is essential to investigate more effective methods and approaches to integrate information and discover knowledge.

Accordingly specific areas that I am interested in working on are as follows;

  • Semantic Web
  • Machine Learning
  • Social Network Analysis
  • Crowdsourcing
Learn More

Research

As social media and networking platforms have become one of major communication platforms as well as an environment for promotion of the ideas for good or bad, they have unprecedented potential to significantly contribute into social and/or political problems to grow by twisting the conflict even more. On the other hand, this potential can be leveraged to contribute into the well-being of societies by providing invaluable insights towards solving these political and/or social conflicts. Small sparks can grow rapidly in a short period of time in a society, and these sparks are usually triggered into a fire with much bigger effect on public communication mediums, which mostly happen to be online social media platforms. Therefore, having the ability of processing and analyzing the data on social media and networking platforms, gains immense importance in terms of the acquisition of knowledge.

Moreover, social media data contains not only text, video or image, but also social metadata such as relationships and interactions, which would play significant roles in making sense of and retrieval of information from the content. The information of social interactions and relationships between users in social media would provide the ability to involve individuals’ influence in their own social networks in measuring its efficacy on the contagion of ideas to be spread over social media. Therefore, measuring individuals’ social networking power and its interplay with the semantic meaning of social data as well as the sentiment to be extracted from the content would increase our ability to understand and describe social and political events in a more realistic manner.

Hence, my motivation in this research is to investigate the computational methodology and approaches that will lead to retrieval of the most possible outcome from social media data. Given the success of the semantic web technologies, social network analysis and machine learning techniques in separate applications over various fields, it is widely considered that social science domain will benefit much from the applications of computational techniques which are being used in computer science. Acquisition of information from social media data and retrieval of knowledge from the acquired information through an interplay of the aforementioned techniques, are critical tasks for achieving the most out of its potential. However, as every domain has its own challenges, the challenges in social computing area will bring also its opportunities that will lead to innovations and let us, as computer scientists, make significant contributions to social data analytics.

Social Computing

Upon the rise of social media in the last decade, social computing area has been evolving based on the needs in processing and analyzing the user-generated content.

Social Media

Social media platforms are mostly communication mediums that enable the users to connect and interact with each other. These platforms are also used to share individuals' ideas, opinions, thoughts on a subject of interest in various longevity depending on the platform.

Data Science

Making sense of social data using machine learning techniques is essential but not sufficient anymore as the characteristics of social data, which becomes mostly user-generated data, is changing.

Big Data

Since users in social media have the liberty to share anything and anytime in any form available, the size of data to handle is usually big, and knowledge discovery also becomes harder to accomplish due to the heterogeneity of data.

Publications

Journal Papers:


  • Amna Basharat, I. Budak Arpinar, Shima Dastgheib, Ugur Kursuncu, Krys Kochut, Erdogan Dogdu. Semantically Enriched Task and Workflow Automation in Crowdsourcing for Linked Data Management. International Journal of Semantic Computing, 8(04), 415-439. 2014.

Conference Papers:


  • I. Budak Arpinar, Dilshod Achilov, Ugur Kursuncu. Social Media Analytics to Identify and Counter Islamist Extremism: Systematic Detection, Evaluation, and Challenging of Extremist Narratives Online. International Conference on Collaboration Technologies and Systems (CTS2016). 2016
  • Amna Basharat, I. Budak Arpinar, Shima Dastgheib, Ugur Kursuncu, Krys Kochut, Erdogan Dogdu. CrowdLink: Crowdsourcing for Large-Scale Linked Data Management. IEEE International Conference on Semantic Computing (ICSC2014). 2014
  • I. Budak Arpinar, Asmita Rahman, Priya Wadhwa, Lakshmish Ramaswamy, Ugur Kursuncu. Semantics-Enabled Proactive and Targeted Dissemination of New Medical Knowledge. 6th International Conference on Bioinformatics and Computational Biology (BICoB2014). 2014

Teaching

I have either taught or been the teaching assistant for the following courses at the University of Georgia.

Data Structures
(Instructor of Record)

I have taught Data Structure course as an Instructor of Record, being responsible for teaching the class, preparing the course material including exams and assignments.

Intro to Programming in Java
(Lab Instructor)

I have taught the lab session of the course, Introduction to Programming in Java, helping students in their hands-on assignments. I have also graded the assignments including exams.

Database Management
(Teaching Assistant)

I had been the teaching assistant for this course providing assistance in helping students in their assignments, grading projects and exams.

Contact Me

Email: kursuncu {at} uga.edu

Address


415 Boyd Graduate Studies Research Center
University of Georgia
Athens, GA 30602

Web