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Who am I? 

My name is Fereshteh Didegah, a PhD holder in Information Science and I am crazy about my job as a researcher in Scientometrics and Almtetrics. 

 What was my PhD thesis about?

I did my PhD in Statistical Cybermetrics Research GroupUK. My thesis was in the area of Scientometrics and I used advanced statistical tests to model the reasons and factors why some articles are highly cited while some others remain uncited for a long time.

Where have I worked so far?

I am currently a postdoctoral researcher at Danish Centre for Studies in Research & Research Policy, Aarhus University, Denmark. I worked at University of Turku, Finland as a postdoctoral researcher for a year in a project on the societal impact of open science. I started doing research in Altmetrics in Finland and published a number of conference/journal papers in this area.







What are my research interests?

My research categories fall into two broad categories: Scientometrics and Altmetrics. My main focus in both areas is on the motivations and reasons for citation counts and altmetric counts. I also like learning new advanced statistical models and using them in my research.

Altmetrics is a new field in imetrics, only 6 years old now. I research different reasons why an article is mentioned on altmetric platforms such as Twitter or Blogs.



My research interests in bibliometrics and scientometrics
  • Citation reasons; citation motivations; citation theory.
  • Different patterns of research collaboration.
  • Research internationality.
  • Research interdisciplinarity.
  • Co-citation and bibliographich coupling analysis.



My research interests in altmetrics

  • Differences between citations and new alternative metrics.
  • Differences between various altmetric platfroms.
  • Altmetric reasons and factors. 
  • Co-network analysis i.e. co-read and co-tweet networks.



My recent research:

In collaboration with Mike Thelwall, we compared three networks with each other: co-citation, co-tweet and co-read networks in order to investigate whether tweeters and Mendeley users tend to tweet or read the same kind of articles that they cite. The results show surprisingly minor overall overlaps between the three phenomena. The importance of journals for Twitter and the presence of many bots at various different levels of activity suggests that this site has little value for impact altmetrics. The moderate differences between patterns of readership and citation suggest that Mendeley can be used for some types of impact assessments, but sensitivity is needed for underlying differences (Didegah, F. & Thelwall, M. (submitted). Co-read, co-tweet, and co-citation networksJournal of the Association for Information Science and Technology)

The is a network of highly co-tweeted journals showing a focus on medical and biomedical journals. 15% of journals are open access indexed in DOAJ.
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