This map shows the geographic impact of Marko Tkalčič's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marko Tkalčič with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marko Tkalčič more than expected).
This network shows the impact of papers produced by Marko Tkalčič. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marko Tkalčič. The network helps show where Marko Tkalčič may publish in the future.
Co-authorship network of co-authors of Marko Tkalčič
This figure shows the co-authorship network connecting the top 25 collaborators of Marko Tkalčič.
A scholar is included among the top collaborators of Marko Tkalčič based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Marko Tkalčič. Marko Tkalčič is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Tkalčič, Marko & Bruce Ferwerda. (2018). Theory-driven Recommendations : Modeling Hedonic and Eudaimonic Movie Preferences. KTH Publication Database DiVA (KTH Royal Institute of Technology). 2140.1 indexed citations
8.
Ferwerda, Bruce & Marko Tkalčič. (2018). You Are What You Post: What the Content of Instagram Pictures Tells About Users’ Personality. KTH Publication Database DiVA (KTH Royal Institute of Technology). 2068.17 indexed citations
9.
Ferwerda, Bruce, Marko Tkalčič, & Markus Schedl. (2017). Personality Traits and Music Genre Preferences : How Music Taste Varies Over Age Groups. KTH Publication Database DiVA (KTH Royal Institute of Technology). 1922. 16–20.16 indexed citations
10.
Ferwerda, Bruce, Mark P. Graus, Andreu Vall, Marko Tkalčič, & Markus Schedl. (2016). The Influence of Users' Personality Traits on Satisfaction and Attractiveness of Diversified Recommendation Lists. TU/e Research Portal. 1680. 43–47.12 indexed citations
11.
Larson, Martha, Andreas Lommatzsch, Domonkos Tikk, et al.. (2016). Algorithms Aside. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 215–219.3 indexed citations
Ferwerda, Bruce, Markus Schedl, & Marko Tkalčič. (2015). Personality & Emotional States: Understanding Users' Music Listening Needs..26 indexed citations
14.
Tkalčič, Marko, Bruce Ferwerda, Markus Schedl, et al.. (2014). Using Social Media Mining for Estimating Theory of Planned Behaviour Parameters.. View.6 indexed citations
15.
Odić, Ante, Marko Tkalčič, J.F. Tasič, & Andrej Košir. (2013). Personality and social context: Impact on emotion induction from movies. View.9 indexed citations
16.
Tkalčič, Marko, et al.. (2013). The Role of Social Signals in Telecommunication: Experimental Design.. View.
17.
Tkalčič, Marko. (2011). Addressing the New User Problem with a Personality Based User Similarity Measure. View.25 indexed citations
18.
Tkalčič, Marko, et al.. (2010). Comparison of an Emotion Detection Technique on Posed and Spontaneous Datasets. View.1 indexed citations
19.
Tkalčič, Marko, et al.. (2009). The LDOS-PerAff-1 Corpus of Face Video Clips with Affective and Personality Metadata. Repository of the University of Ljubljana (University of Ljubljana).8 indexed citations
20.
Tkalčič, Marko, et al.. (2003). The IEEE Region 8 EUROCON 2003, computer as a tool : 22-24 September 2003, Faculty of Electrical Engineering, University of Ljubljana, Ljubljana, Slovenia : proceedings.1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.