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  • Expression of Interest

    Middle East Technical University, Computer Eng. Dept.

    Pinar Karagoz is co-leading the Data Mining research group in METU Computer Eng. Dept. Her recent research focuses in text mining and social media analysis, including sentiment analysis, irony detection, event detection and personality analysis problem. Explainability analyis on text mining is another related research topic studied by the research group and herself. Some of the related publications by the research group are as follows:


    Mavis, G., Toroslu, I. H., & Karagoz, P. (2021). Personality Analysis Using Classification on Turkish Tweets. International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), 15(4), 1-18.

    Ozturk, A. U., Cemek, Y., & Karagoz, P. (2021). IronyTR: Irony Detection in Turkish Informal Texts. International Journal of Intelligent Information Technologies (IJIIT), 17(4), 1-18.

    Buyukbas E.B., Dogan A.H., Ozturk A.U., Karagoz P. (2021) Explainability in Irony Detection. In: Golfarelli M., Wrembel R., Kotsis G., Tjoa A.M., Khalil I. (eds) Big Data Analytics and Knowledge Discovery. DaWaK 2021. Lecture Notes in Computer Science, vol 12925. Springer, Cham.

    Demirci, M. U., Karagoz, P., Trust Modeling in Recommendation: Explicit and Implicit Trust Model Compatibility and Explicit Trust Prediction, Proceedings of the 13th International Conference on Management of Digital EcoSystems, 2021.

    Aktunc, R., Toroslu, I. H, Karagoz, P. , Event Detection on Communities: Tracking the Change in Community Structure within Temporal Communication Networks, Putting Social Media and Networking Data in Practice for Education, Planning, Prediction and Recommendation pp 75-96.

    Gun, A., Karagoz, P., A Hybrid Approach for Credibility Detection in Twitter, International Conference on Hybrid Artificial Intelligence Systems (HAIS 2014),  pp 515-526




    Pinar Karagoz has taken part in  the COST Action projects ENERGIC (IC1203) and Underground4Valorisation (CA18110). She has been actively working with multidisciplinary teams within U4V project. 

    As the research group we would like to contribute to project proposals with our experties on text mining and social network analysis.