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  • 140 Citations
  • 7 h-Index
20132020

Research output per year

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Personal profile

Biography

Yannis is a Reader in Computer Science, with a research focus on a variety of subfields of Natural Language Processing and Text Mining, such as compositional semantics, multiword expression and term extraction, document classification and sentiment analysis, applied to a number of domains, such as biomedicine, social sciences, social media, open source software and scientific publications.

Yannis holds a PhD in Computer Science from the University of York, an MPhil in Computer Text, Speech and Internet Technology from the University of Cambridge and a first class honours Diploma in Electrical and Computer Engineering from the National Technical University of Athens, Greece.

Prior to joining the Department of Computer Science, Edge Hill University, he was employed as a Research Fellow at the National Centre for Text Mining (NaCTeM), University of Manchester. Among other projects, he was involved in the development, write up and successful completion of OSSMETER, an EU FP7 STReP project that developed an innovative platform for automatically analysing and measuring open-source software to support decision makers in the process of discovering, comparing, assessing and monitoring the health, quality, impact and activity of open-source software. He was also involved in ISHER (Integrated Social History Environment for Research – Digging into Social Unrest), one of the 14 projects that won the second Digging Into Data Challenge (JISC) in 2011. The project resulted in an integrated environment that indexes all articles published in the New York times in 20 years. The environment can be used as a novel exploratory tool for scientists to answer research questions quickly and accurately.

Research interests

Natural Language Processing, Text Mining, Social media analysis, Machine Learning

Teaching

  • Big Data
  • Applications in Big Data

Education/Academic qualification

DipEng Electrical & Computer Engineering, Other, National Technical University of Athens

Computer Speech, Text and Internet Technology, MPhil, University of Cambridge

Computer Science, PhD, University of York

Other positions

Research Fellow, University of Manchester

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Research Output

  • 140 Citations
  • 7 h-Index
  • 9 Article
  • 5 Paper
  • 2 Conference proceeding (ISBN)

Classifying emotions in Stack Overflow and JIRA using a multi-label approach

CABRERA DIEGO, LUIS. ADRIAN., BESSIS, NIKOLAOS. & KORKONTZELOS, YANNIS., 14 Feb 2020, In : Knowledge-Based Systems. 105633

Research output: Contribution to journalArticle

Open Access
File
  • 19 Downloads (Pure)

    Efficient treatment of outliers and class imbalance for diabetes prediction

    NNAMOKO, NONSO. & KORKONTZELOS, YANNIS., 10 Feb 2020, In : Artificial Intelligence in Medicine (AIIM). 104, 101815

    Research output: Contribution to journalArticle

    Open Access
    File
  • Open Access
    File
  • 1 Citation (Scopus)
    56 Downloads (Pure)

    A Multinomial Logistic Regression Approach for Arrhythmia Detection

    Behadada, O., Trovati, M., Kontonatsios, G. & Korkontzelos, Y., 31 Dec 2018, In : International Journal of Distributed Systems and Technologies (IJDST). 8, 4, p. 17-33

    Research output: Contribution to journalArticle

  • Detection of spam-posting accounts on Twitter

    Inuwa-Dutse, I., Liptrott, M. & Korkontzelos, Y., 8 Aug 2018, In : Neurocomputing. p. 1-38

    Research output: Contribution to journalArticle

    Open Access
    File
  • 18 Citations (Scopus)
    68 Downloads (Pure)

    Activities

    • 2 Invited talk

    BigComp

    YANNIS KORKONTZELOS (Speaker)
    2015

    Activity: Talk or presentation typesInvited talk

    Mining Big Text Workshop

    YANNIS KORKONTZELOS (Speaker)
    2015

    Activity: Talk or presentation typesInvited talk

    Thesis

    Detection of Microcosms on Twitter

    Author: INUWA-DUTSE, I., 7 Jan 2020

    Supervisor: KORKONTZELOS, Y. (Director of Studies), RIZZUTO, F. (Supervisor) & LIPTROTT, M. (Supervisor)

    Student thesis: Doctoral Thesis

    File