Published articles

  1. Trzcinski T., Bielski A., Cyrta P., Zak M., SocialML: machine learning for social media video creators, Neural Information Processing Systems Conference (NIPS) 2017 – Workshop on Machine Learning for Creativity and Design, Long Beach, California, USA, December 8, https://nips2017creativity.github.io/doc/SocialML.pdf
  2. Morzy M., Kajdanowicz T., Kazienko P. (2017), On Measuring the Complexity of Networks: Kolmogorov Complexity vs. Entropy, Complexity, https://www.hindawi.com/journals/complexity/2017/3250301.
  3. Toruniewska J., Kułakowski K., Suchecki K., Hołyst J.A.(2017), Coupling of link- and node-ordering in the coevolving voter model, Physical Review E, Vol. 96, No. 4, 042306, http://arxiv.org/abs/1711.09004
  4. Bartusiak R., Augustyniak Ł., Kajdanowicz T., Kazienko P., Piasecki M. (2017), WordNet2Vec: Corpora Agnostic Word Vectorization Method, Neurocomputing, http://www.sciencedirect.com/science/article/pii/S0925231217315217
  5. Jankowski J., Bródka P., Michalski R., Kazienko P. (2017),  Seeds Buffering in Information Spreading Processes. SocInfo2017 – 9th International Conference on Social Informatics. Oxford, UK, September 13-15, Lecture Notes on Computer Science LNCS , Springer, 2017, Available at: https://arxiv.org/abs/1709.04863
  6. Jankowski, J., Bródka, P., Kazienko, P., Szymanski, B., Michalski, R., & Kajdanowicz, T. (2017), Balancing Speed and Coverage by Sequential Seeding in Complex Networks, Scientific Reports, vol. 7, art. 891.  Available at: https://www.nature.com/articles/s41598-017-00937-8
  7. Augustyniak Ł., Rajda K., Kajdanowicz T. (2017), Method for aspect-based sentiment annotation using rhetorical analysis, 9th Asian Conference, ACIIDS 2017, Kanazawa, Japan, April 3-5, Proceedings, Part I, pp 772-781, Available at:  https://link.springer.com/chapter/10.1007/978-3-319-54472-4_72  and on arxiv
  8. Morzy M., Kajdanowicz T., Szymański B. (2016), Benford’s distribution in complex networks, Scientific Reports, vol. 6, art. 34917. Available at: http://www.nature.com/articles/srep34917.
  9. Chołoniewski J., Leban G., Macek S., Rehar A.(2016), Information flow between news articles: Slovene media case study, Informatica. An International Journal of Computing and Informatics, D, 13-16.  Available at: http://ailab.ijs.si/dunja/SiKDD2016/Papers/Choloniewski_InformationFlow.pdf
  10. Gajewski Ł.G., Chołoniewski J., Hołyst, J. A. (2016), Key Courses of Academic Curriculum Uncovered by Data Mining of Students’ Grades, ACTA PHYSICA POLONICA A, Vol. 129, no. 5, http://www.if.pw.edu.pl/~jholyst/data/a129z5p32.pdf
  11. Szymański, P., Kajdanowicz, T., & Kersting, K. (2016), How Is a Data-Driven Approach Better than Random Choice in Label Space Division for Multi-Label Classification? Entropy, 18(8), 282. Available at: http://doi.org/10.3390/e18080282

Accepted

  1. Herga Z., Doyle C., Dipple S., Nasman C., Korniss G., Szymanski B., Brank J., Rupnik J., Mladenic D., Building Client’s Risk Profile Based on Call Detail Records, accepted at SiKDD conference (https://is.ijs.si/gallery_detailed.php?id=5)
  2. Klemiński R., Kazienko P., Identifying Promising Research Topics in Computer Science, 4th European Network Intelligence Conference – 11.-12. September 2017, Duisburg.
  3. Jankowski J., Michalski R., Bródka P., A multilayer network dataset of interaction and influence spreading in a virtual world, accepted to Scientific Data (01.08.2017), https://arxiv.org/abs/1702.06373.
  4. Kajdanowicz T., Tagowski K., Falkiewicz M., Kazienko P., Incremental Learning in Dynamic Networks for Node Classification, 4th European Conference on Network Intelligence, Duisburg, Germany, in press, 2017.
  5. Erlandsson F., Bródka P., Borg A., Seed selection for information cascade in multilayer networks, The 6th International Conference on Complex Networks and Their Applications, November 29 – December 01 2017 Lyon,  France, https://arxiv.org/abs/1710.04391

Submitted

  1. Paluch, R., Suchecki, K., Lu, X., Szymański, B. K., Hołyst, J. A., Fast and accurate detection of spread source in large complex networks, submitted to Scientific Reports,
  2. Czaplicka A., Hołyst, J. A., From equality to diversity – bottom-up approach for hierarchy growth, submitted to Physical Review E, https://arxiv.org/abs/1707.00985
  3. Sienkiewicz J., Soja K., Hołyst, J. A., Sloot P. M. A.,  Categorical and Geographical Separation in Science, submitted to Scientific Reports,
  4. Krawczyk M., Kułakowski K., Hołyst, J. A., Consecutive partitions of social networks between rivalling leaders, submitted to PLOS ONE  https://arxiv.org/pdf/1611.05604.pdf

Under Preparation

  1. Paluch R., Chołoniewski J., Suchecki K., Hołyst, J.A., Leban, G., Fuart, F., Karlovcec, M., Rupnik, J., Grobelnik,M., Hoekstra, A., Sloot, P., Sobkowicz, P.,  Toczyski, P., Does the rise of new media explain the expansion of old media coverage ?
  2. Kajdanowicz T., Kazienko P., Popiel A., Chawla N., Fusion Methods for Node Classification in Multiplex Networks
  3. Morzy M., Kajdanowicz T., Kazienko P., Miebs G., and Rusin A., Priority Rank: Universal Network Model for Generating Synthetic and Re-creating Empirical Networks, in preparation, to be submitted to Scientific Reports, 2017.
  4. Erlandsson F., Bródka P., Boldt M., Johnson H., Do we really need to catch them all? A new User-guided Social Media Crawling method.
  5. Michalski R., Szymanski B.K., Kazienko P., Lebiere C., Lizardo O., Kulisiewicz M.: Temporal Social Networks Through the Prism of Cognition.