I am an assistant professor of Computer Science at the Department of Computational Intelligence, Wroclaw University of Science and Technology. I have received MSc in Computer Science from the Wroclaw University of Technology, Poland in 2008 and PhD in 2012. I was a visiting scholar at Stanford University in 2013. I have authored over 60 scholarly and research articles on a variety of areas related to complex networks, focusing on the extraction and dynamics of communities within social networks, spreading processes in complex networks and the analysis of multilayer network. In 2015 I have received 3 years scholarship for the best young scientists awarded by Polish Ministry of Science and Higher Education. You can meet me at most of top conferences on social networks and social informatics e.g.: NetSci, NetSciX, IC2S2, ASONAM, SocInfo etc.

My PhD thesis topic was A Method for Group Extraction and Analysis in Multilayer Social Networks , so as I have already mentioned one of my research area is communities within complex social networks, their evolution, analysis and prediction of their future behaviour.

CV : PL | ENG

Main research areas

Complex Networks
Social Network Analysis
Dynamic of Social Networks
Spreading Proceses in Complex Networks, Especially Multilayer Netwoks
Multilayer Social Networks
Group Extraction in Multilayer Social Networks
Group Analysis in Multilayer Social Networks
Group Dynamic in Multilayer Social Networks


Books and Book Chapters

  1. Saganowski S., Bródka P., Kazienko P.: Community Evolution. Encyclopedia of Social Network Analysis and Mining pp 1-14 Springer New York 2017, doi 10.1007/978-1-4614-7163-9_223-1
    arXiv.org:1605.00069
  2. Bródka P., Kazienko P.: Multi-layered social networks. Encyclopedia of Social Network Analysis and Mining. Volume 2. Springer, 2014, pp. 998-1013
    arXiv.org:1212.2425v1
  3. Bródka P., Saganowski S., Kazienko P.: Community Evolution. Encyclopedia of Social Network Analysis and Mining. Volume 1. Springer, 2014, pp. 220-232.
    arXiv.org:1605.00069
  4. Bródka P. A Method for Group Extraction and Analysis in Multilayer Social Networks Ph.D. disertation, Wrocław, Poland, 2012
    arXiv.org:1302.1369
  5. Bródka P. Key Users in Social Network. How to find them? LAP Lambert Academic Publishing, 2012, ISBN-13: 978-3-659-19597-6, ISBN-10: 3659195979
    arXiv.org:1302.1369
  6. Filipowski T., Bródka P., Kazienko P.: EcoRide - the social-based system for car traffic optimization. Chapter in Green Technologies and Business Practices: An IT Approach. IGI-Global,August 2012, DOI: 10.4018/978-1-4666-1972-2
  7. Kazienko P., Bródka P.: Data Warehouses, Published by PRINTPAP Łódz, Wrocław 2011, ISBN 978-83-62098-97-2

Articles in the International Journals

  1. Jankowski J., Michalski R., Bródka P.: How we interact and influence each other in virtual worlds: spreading processes in multilayer complex network
    PDF
  2. Erlandsson F., Bródka P., Boldt M., Johnson H.: Do we really need to catch them all? A new User-guided Social Media Crawling method
    PDF
  3. Jankowski J., Bródka P., Kazienko P., Szymanski B., Michalski R., Kajdanowicz T.: Balancing Speed and Coverage by Sequential Seeding in Complex Networks Scientific Reports, 7(1), 891, DOI: 10.1038/s41598-017-00937-8
    PDF
  4. Jankowski J., Bródka P., Humari J.: A Picture is Worth a Thousand Words: An Empirical Study on the Influence of Content Visibility on Diffusion Processes within a Virtual World. Behaviour & Information Technology, Volume 35, 2016 - Issue 11, Pages 926-945, DOI:10.1080/0144929X.2016.1212932
    PDF
  5. Jankowski, J., Saganowski, S., Bródka, P. Evaluation of TRANSFoRm mobile eHealth solution for remote patient monitoring during clinical trials. Mobile Information Systems, Volume 2016 (2016), Article ID 1029368, 16 pages
    PDF
  6. Erlandsson F., Bródka P., Borg A., Johnson H.: Finding Influential Users in Social Media Using Association Rule Learning. Entropy Special Issue "Machine Learning and Entropy: Discover Unknown Unknowns in Complex Data Sets" 2016, 18(5), 164; doi:10.3390/e18050164
    PDF
  7. Mastellos N., Bliźniuk G., Czopnik D., McGilchrist M., Misiaszek A., Bródka P., Curcin V., Car J., Delaney B., Andreasson A.: Feasibility and acceptability of TRANSFoRm to improve clinical trial recruitment in primary care. Family Practice (2016) 33 (2): 186-191. doi: 10.1093/fampra/cmv102
    PDF
  8. Saganowski S., Bródka P., Misiaszek A., Fraczkowski K.: Mobile eHealth solution (ePRO). Journal of Clinical Bioinformatics. 2015, 5(Suppl 1):S14 doi:10.1186/2043-9113-5-S1-S14
    PDF
  9. Saganowski S., Gliwa B., Bródka P., Zygmunt A., Kazienko P., Koźlak J.: Predicting Community Evolution in Social Networks. Entropy 2015, 17, 3053-3096; doi:10.3390/e17053053
    PDF
  10. Różewski P., Jankowski J., Bródka P., Michalski R.: Knowledge workers’ collaborative learning behavior modeling in an organizational social network. Computers in Human Behavior, Volume 51, Part B, October 2015, Pages 1248–1260, doi:10.1016/j.chb.2014.12.014
    arXiv:1505.03055
  11. Jankowski J., Michalski R., Bródka P., Kazienko P., Utz S.: Knowledge Acquisition from Social Platforms Based on Network Distributions Fitting. Computers in Human Behavior, Volume 51, Part B, October 2015, Pages 1248–1260, doi:10.1016/j.chb.2014.12.015
    arXiv:1505.03049
  12. Musial K., Bródka P., Kazienko P., Gaworecki J.: Extraction of Multi-layered Social Networks from Activity Data.The Scientific World Journal. Volume 2014 (2014), Article ID 359868, 13 pages.
    PDF
  13. Michalski R., Kajdanowicz T., Bródka P., Kazienko P.: Seed Selection for Spread of Influnece in Social Networks: Temporal vs. Static Approach. New Generation Computing, Vol. 32, Nos. 3-4, 2014, pp. 213-235.
    arXiv.org:1405.0538
  14. Bródka P., Saganowski S., Kazienko P.: GED: The Method for Group Evolution Discovery in Social NetworksSocial Network Analysis and Mining, March 2013, Volume 3, Issue 1, pp 1-14, DOI:10.1007/s13278-012-0058-8
    arXiv.org:1207.4297
  15. Saganowski S., Bródka P., Kazienko P.: Influence of the User Importance Measure on the Group Evolution Discovery. Foundations of Computing and Decision Sciences, Volume 37, Issue 4, Pages 293-303, 2012.
    arXiv.org:1301.1534
  16. Bródka P., Kazienko P., Musiał K., Skibicki K., Analysis of Neighbourhoods in Multi-layered Dynamic Social Networks.International Journal of Computational Intelligence Systems, vol. 5, no. 3, 2012 pp. 582-596.
    arXiv.org:1207.4293
  17. Zygmunt A., Bródka P., Kazienko P., Koźlak J.: Key Person Analysis in Social Communities within Blogosphere. Journal of Universal Computer Science, vol. 18, no. 4, 2012, pp. 577-597.
    JUCS18(4)
  18. Filipowski T., Kazienko P., Bródka P., Kajdanowicz T.: Web-based knowledge exchange through social links in the workplace. Behaviour and Information Technology 2012, vol. 31, nr 8, s. 779-790, doi: 10.1080/0144929X.2011.642895
  19. Kukla G., Kazienko P., Bródka P., Filipowski T.: SocLaKE - Social Latent Knowledge Explorator, The Computer Journal, Vol. 55 No. 3, 2012, pp. 258-276, doi: 10.1093/comjnl/bxr093
    Reprint
  20. Palus S., Bródka P., Kazienko P.: Evaluation of Organization Structure based on Email Interactions, International Journal of Knowledge Society Research, Vol. 2, No. 1, 2011, pp. 1-13.
    Reprint
  21. Kazienko P., Ruta D., Bródka P.: The Impact of Customer Churn on Social Value Dynamics, International Journal of Virtual Communities and Social Networking, 1(3), July-September 2009, 60-72.
    Reprint

International Conferences

    2016

  1. Erlandsson F., Bródka P., Borg A., Johnson H.: Finding Influential Users in Social Media Using Rule Learning Second International Conference on Computational Social Science IC2S2, Northwestern University, June 2016
  2. Saganowski S., Misiaszek A., Bródka P., Andreasson A., Curcin V., Delaney B., Frączkowski K.: TRANSFoRm eHealth solution for quality of life monitoring AMIA 2016 Summit on Clinical Research Informatics, CRI 2016, March 21-24, 2016, 2016, San Francisco, CA, pp. 231-239
  3. Erlandsson F., Borg A., Johnson H., Bródka P.: Predicting User Participation in Social Media. NetSciX 2016 - International School and Conference on Network Science, January 11-13, 2016, Wroclaw, Poland, LNCS Advances in Network Science Volume 9564 pp 126-135
  4. 2015

  5. Jankowski J., Michalski R., Kazienko P., Bródka P., Utz S.: Adaptive Survey Design Using Structural Characteristics of the Social Networkg. SocInfo 2015 - The 7th International Conference on Social Informatics, Beijing, China, December 9-12, 2015, Proceedings (Vol. 9471, p. 153). Springer.
  6. Michalski R., Kajdanowicz T., Bródka P., Piotr Bródka, Przemysław Kazienko Kazienko P.: Spread of Influence in Temporal Networks. IC2S2 2015 - INTERNATIONAL CONFERENCE ON COMPUTATIONAL SOCIAL SCIENCE, June 8-11, 2015, Helsinki, Finland
  7. Bródka P., Kazienko P.: Group Extraction in Multi-layered Social Network. NetSci 2015 - International School and Conference on Network Science, June 1-5, 2015, Zaragoza, Spain
  8. Lim Choi Keung S.N, Zhao L., Curcin V, Ethier J-F., Burgun A., McGilchrist M., Bródka P., Tuligłowicz W., Andreasson A., Delaney B.C., Arvanitis T.N.TRANSFoRm: Implementing a Learning Healthcare System in Europe through Embedding Clinical Research into Clinical Practice, ICSS2014 - 48th Annual Hawaii International Conference on System Sciences, IEEE Computer Society Press
    PDF

  9. 2014

  10. Bródka P., Sobas M., Johnson H.: Profile Cloning Detection in Social Networks. The First European Network Intelligence Conference, September 29-30, 2014, Wroclaw, Poland, IEEE Computer Society, pp. 63-68
  11. Michalski, R., Jankowski J., Bródka P., Kazienko P.: The Same Network - Different Communities? The Multidimensional Study of Groups in the Cyberspace. SNAA 2014 - the 4th Workshop on Social Network Analysis in Applications at ASONAM 2014 - The 2014 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining, Beijing, China, August 17-20, 2014, IEEE, 2014,
  12. Michalski, R., Kazienko P., Kajdanowicz T., Bródka P.: Data-driven Seed Selection for Spread of Influence in Temporal Social Networks. Workshop on Sociophysics at SigmaPhi 2014 - The International Conference on Statistical Physics 2014, Rhodes, Greece, July 7-11, 2014, Kaniadakis G., Scarfone A.M. (eds.), 2014, p. 75.
  13. Saganowski S., Gliwa B., Bródka P., Zygmunt A., Kazienko P., KozŸlak J.: Predicting Community Evolution in Social Networks, poster. NetSci 2014 - International School and Conference on Network Science
  14. Michalski R., Kajdanowicz T., Bródka P., Kazienko P.: Seed Selection in Social Networks - Temporal Approach Benefits. TnetSphys'14 - Temporal Networks, Human Dynamics and Social Physics Symposium at NetSci 2014 - International School and Conference on Network Science
  15. Frączkowski K., Bródka P., Misiaszek A., Saganowski S., Kazienko P.: The mobile system supporting health safety of patients in the TRANSFoRm project. Workshop: CRI Solution Day
  16. Brodka P, Kazienko P, Andreasson A, Fraczkowski K, Misiaszek A, Saganowski S, Zhao L, Curcin V, Arvanitis T, Delaney B, Michalski R.: Remote Patient Health Condition Monitoring for Clinical Research. 19th WONCA Europe Conference, Lisbon, 3 July 2014.
  17. Curcin V, Arvanitis T, Ethier J-F, Fraczkowski K, Kazienko P, Brodka P, Andreasson A, Blizniuk G, Lim Choi Keung S, Zhao L, Misiaszek A, McGilchrist M, Burgun A, Delaney B. Semantic Approach to Achieving Interoperability between Clinical Care and Clinical Research. 19th WONCA Europe Conference, Lisbon, 3 July 2014.
  18. Curcin V., Arvanitis T.N., Brodka P., Corrigan D., Delaney B.: TRANSFoRm digital infrastructure: The architecture for The Learning Healthcare System in Europe AMIA 2014 Clinical Research Informatics Summit Panel

  19. 2013

  20. Gliwa B., Bródka P., Zygmunt A., Saganowski S., Kazienko P., Koźlak J.: Different Approaches to Community Evolution Prediction in Blogosphere. SNAA 2013 at ASONAM 2013, IEEE Computer Society, 2013, pp. .
  21. Kazienko P., Kajdanowicz T., Michalski R., Bródka P.: From Data to Human Behaviour. SOCIETY 2013, IEEE Computer Society, 2013, pp. .
  22. Kajdanowicz T., Filipowski T, Kazienko P., Bródka P. Competence Region Modelling in Relational ClassificationACIIDS 2013, LNCS 7803, 2013, pp 236-244.
  23. Bródka P., Filipowski T., Kazienko P.: An Introduction to Community Detection in Multi-layered Social Network , WSKS 2011, CCIS 278, Springer, pp 185-190, 2012.
    arXiv.org:1209.6050
  24. Saganowski S., Bródka P., Kazienko P.: Influence of the Temporal Social Network Timeframe Type and Size on Tracking Group Evolution. Workshop on Temporal and Dynamic Networks: From Data to Models at NetSci 2013
  25. Michalski R., Jankowski J., Bródka P., Kazienko P.: How the Network Dynamics Influences the Diffusion of Innovations. Workshop on Temporal and Dynamic Networks: From Data to Models at NetSci 2013
  26. Bródka P., Kazienko P., Saganowski S., Michalski R.: Quantifying Multi-layered Complex Networks. Satellite Symposium on Multiple Network Modeling, Analysis and Mining at NetSci 2013

  27. 2012

  28. Bródka P., Kazienko P., Kołoszczyk B.: Predicting Group Evolution in the Social Network. SocInfo 2012, LNCS 7710, Springer, 2012, pp. 54–67.
    arXiv.org:1210.5161
  29. Michalski R., Bródka P., Kazienko P., Juszczyszyn K.: Quantifying Social Network Dynamics. CASoN 2012, IEEE Computer Society, 2012, pp. 69-74.
    arXiv.org:1303.5009
  30. Saganowski S., Bródka P., Kazienko P.: Influence of the Dynamic Social Network Timeframe Type and Size on the Group Evolution Discovery. ASONAM 2012, IEEE Computer Society, 2012, pp. 678-682.
    arXiv.org:1210.5167
  31. Gliwa B., Saganowski S., Zygmunt A., Bródka P., Kazienko P., Koźlak J.: Identification of GroupChanges in Blogosphere. ASONAM 2012, IEEE Computer Society, 2012, pp. 1233-1238.
    arXiv.org:1210.5171
  32. Bródka P., Saganowski S., Kazienko P.: Group Evolution Discovery in Social Networks. NetSci 2012

  33. 2011

  34. Bródka P., Saganowski S., Kazienko P.: Tracking Group Evolution in Social Networks. SocInfo 2011, Lecture Notes in Artificial Intelligence LNAI , Springer, 2011, pp. 316-319. Best Demo\Poster\Paper Award Fotografie 1, 2 i 3 z ceremoni wręczenia nagrody.
    arXiv.org:1210.5240
  35. Michalski R., Palus S., Kazienko P., Bródka P., Juszczyszyn K.: Modelling Social Network Evolution. SocInfo 2011, Lecture Notes in Artificial Intelligence LNAI , Springer, 2011, pp. 283-286
  36. Bródka P., Skibicki K., Kazienko P., Musiał K.: A Degree Centrality in Multi-layered Social Network. CASoN 2011, IEEE Computer Society, 2011, pp. 237-242
    arXiv.org:1210.5184
  37. Bródka P., Saganowski S., Kazienko P.: Group Evolution Discovery in Social Networks, ASONAM 2011, IEEE Computer Society, 2011, pp. 247-253
  38. Bródka P., Stawiak P., Kazienko P.: Shortest Path Discovery in the Multi-layered Social Network, ASONAM 2011, IEEE Computer Society, 2011, pp 497-501
    arXiv.org:1210.5180
  39. Zygmunt A., Bródka P., Kazienko P., Koźlak J.: Different Approaches to Groups and Key Person Identification in Blogosphere, SNAA 2011 at ASONAM 2011, IEEE Computer Society, 2011, pp. 593-598
  40. Kazienko P., Musial K., Kukla E., Kajdanowicz T., Bródka P.: Multidimensional Social Network: Model and Analysis, ICCCI 2011, Lecture Notes in Artificial Intelligence LNAI, Springer, 2011, pp. 378-387.
  41. Kazienko P., Kukla E., Musial K., Kajdanowicz T., Bródka P., Gaworecki J.: A Generic Model for Multidimensional Temporal Social Network, ICeND2011, CCIS 171, Springer, 2011, pp. 1-14
  42. Popowicz D., Bródka P., Kazienko P., Kozielski M.: Ask Your Friends for Help: A Collaborative Query Answering System, CDVE2011, Lecture Notes in Computer Science, Springer, 2011, pp. 110-113

  43. 2010

  44. Kukla G., Kazienko P., Bródka P., Filipowski T.: Recommendation Boosted Query Propagation in the Social Network, SocInfo 2010, Lecture Notes in Artificial Intelligence LNAI , Springer, 2010, pp. 113-124
  45. Kazienko P., Bródka P., Musial K., Gaworecki J.: Multi-layered Social Network Creation Based on Bibliographic Data , SocialCom2010, IEEE Computer Society Press, 2010, pp. 407-412
  46. Juszczyszyn K., Musiał A., Musiał K., Bródka P.: Utilizing Dynamic Molecular Modelling Technique for Predicting Changes in Complex Social Networks, 2010 IEEE/WIC/ACM, IEEE Computer Society Press, 2010, pp. 1-4
  47. Kazienko P., Bródka P., Musiał K.: Individual Neighbourhood Exploration in Complex Multi-layered Social Network, 2010 IEEE/WIC/ACM, IEEE Computer Society Press, 2010, pp. 5-8
  48. Bródka P., Musial K., Kazienko P.: A Method for Group Extraction in Complex Social Networks., WSKS 2010, CCIS 111, Springer, 2010, pp. 238-247.
  49. Palus S., Bródka P., Kazienko P.: How to Analyze Company Using Social Network?, WSKS 2010, CCIS 111, Springer, 2010, pp. 159-164.

  50. 2009

  51. Bródka P., Musiał K., Kazienko P.: Efficiency of Node Position Calculation in Social Networks, KES 2009, LNCS/LNAI, Springer, 2009, pp.455-463
  52. Bródka P., Musiał K., Kazienko P.: A Performance of Centrality Calculation in Social Networks, CASoN 2009, IEEE Computer Society, 2009, pp.24-31.
  53. Musiał K., Kazienko P., Bródka P.:User position measures in social networks SNA-KDD 2009
  54. Ruta D., Kazienko P., Bródka P.: Network-Aware Customer Value in Telecommunication Social Networks, ICAI 09, CSREA Press, pp. 261-267.
  55. Kazienko P., Bródka P., Ruta D.: The Influence of Customer Churn and Acquisition on Value Dynamics of Social Neighbourhoods, WSKS 2009, LNCS/LNAI, Springer, 2009, pp.491-500
  56. Juszczyszyn K., Musiał A., Musiał K., Bródka P.: Molecular Dynamics Modelling of the Temporal Changes in Complex Networks, CEC 09, IEEE Computer Society Press, 2009 pp. 553-559.

Polish National Conferences

  1. Bródka P., Kaim K.: Badanie logów serwera Politechniki Wrocławskiej metodami eksploracji danych, Oficyna Wydawnicza Politechniki Wrocłwskiej, V Konferencja naukowa studentółw Referaty Tom 1, str. 49-54.
  2. Bródka P.: Indeksowanie obiektółw wielowymiarowych, Oficyna Wydawnicza Politechniki Wrocławskiej, IV Konferencja naukowa studentów Referaty Tom 1, str. 79-84.

Program Committee

  1. EXECUTIVE CHAIR of NetSciX 2016 - International School and Conference on Network Science, Wrocław, Poland, 11-13 January 2016
  2. SocialCom 2015 - The 8th IEEE International Conference on Social Computing and Networking, Chengdu, China, 19-21 December 2015
  3. MANEM'15 - First International workshop on Multiplex & Attributed Network Mining, Paris, 25 August 2015
  4. MISNC 2015 - The 2nd International Multidisciplinary Social Networks Conference, Dogo, Matsuyama City, Ehime, Japan, September 1-3, 2015
  5. SocInfo 2015 - The 7th International Conference on Social Informatics. Beijing, 9-12 December 2015.
  6. BigData 2015 - The Fifth ASE International Conference on Big Data, October 7-9, 2015, Kaohsiung, Taiwan
  7. Socialinformatics 2015 - The Fourth ASE International Conference on Social Informatics, October 7-9, 2015, Kaohsiung, Taiwan
  8. SOTICS 2015 - The Fifth International Conference on Social Media Technologies, Communication, and Informatics, November 15 - 20, 2015, Barcelona, Spain
  9. IEEE DSAA 2015 - 2015 IEEE International Conference on Data Science and Advanced Analytics, October 19-21, 2015, Paris, France
  10. Chair of ENIC 2015 - The Second European Network Intelligence Conference, September 21-22, 2015 – Karlskrona, Sweden
  11. Chair of SNAA 2015 - The 5th Workshop on Social Network Analysis in Applications, Paris, France, August 25-28, 2015
  12. AMIA 2015 Joint Summits on Translational Science, San Francisco CA, March 23-27, 2015
  13. SI 2014 - Workshop on Social Influence, collocated with SocInfo 2014, November 10, Barcelona, Spain
  14. Co - founder ENIC 2014 - The First European Network Intelligence Conference, September 29-30, 2014 - Wroclaw, Poland
  15. ASONAM 2014 - The 2014 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining, Beijing, China, August 17-20, 2014.
  16. Chair of SNAA 2014 - The 4th Workshop on Social Network Analysis in Applications, Beijing, China, August 17, 2014
  17. DCOSS 2014 - IEEE International Conference on Distributed Computing in Sensor Systems, Marina Del Rey, California, May 26 - 28 2014
  18. SocInfo 2014 - The 6th International Conference on Social Informatics. Barcelona, 10-13 November 2014.
  19. COMPSAC 2014 - 38th Annual International Computers, Software & Applications Conference, Västerås, Sweden 21–25 July, 2014
  20. IICST 2014 - Innovations in Information and Communication Science and Technology, September 3-5, 2014, Warsaw, Poland
  21. DSAA 2014 - 2014 International Conference on Data Science and Advanced Analytics, October 30 - November 1, 2014, Shanghai, China
  22. SoNAEdu 2014 - The International Workshop on Social Networks and its Applications on Education Beijing, China, August 4, 2014 (SocialCom2014)
  23. SOTICS 2014 - The Fourth International Conference on Social Eco-Informatics October 12 - 16, 2014 - Nice, France
  24. Publicity Chair MISNC 2014 - The 2014 Multidisciplinary International Social Networks Conference, Kaohsiung, Taiwan, September 13-14, 2014
  25. ACIIDS 2014 - The 6th Asian Conference on Intelligent Information and Database Systems April 7 - 9, 2014, Bangkok, Thailand
  26. Chair of SNAA 2013 - The Third Workshop on Social Network Analysis in Applications, 25-28 August, 2013, Niagara Falls, Canada
  27. SocInfo 2013 - The 5th International Conference on Social Informatics (SocInfo2013), 25–27 November 2013, Kyoto, Japan.
  28. ASONAM 2013 - The 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 25-28 August, 2013, Niagara Falls, Canada
  29. Program Char of SNAA 2013 - The Third Workshop on Social Network Analysis in Applications, 25-28 August, 2013, Niagara Falls, Canada
  30. SOTICS 2013 - The Third International Conference on Social Eco-Informatics, November 17 - 22, 2013 - Lisbon, Portugal
  31. ASONAM 2012 - The 2012 International Conference on Advances in Social Networks Analysis and Mining, 26-29 August, 2012, Kadir Has University, Istanbul, Turkey
  32. SOTICS 2012 - The Second International Conference on Social Eco-Informatics, October 21 - 26, 2012 - Venice, Italy
  33. EWCIP 2012 - II European Workshop on Computing and ICT Professionalism. Associated to the 7th Iberian Conference on Information Systems and Technologies. 20th - 23rd June 2012, Madrid, Spain
  34. INBAST 2012 - 2nd Workshop on Industrial and Business Applications of Semantic Web Technologies. Associated to the OnTheMove Federated Conferences and Workshops OTM 2012. 10.-14.9.2012, Rome, Italy

Scolarships and awards

  1. Fellowship fot the best young scientists awarded by Polish Ministry of Science and Higher Education
  2. Fellowship co-Financed by European Union within European Social Fund for Young Scientists Młoda Kadra 2015 Plus 2014/2015 (IV edycja)
  3. Fellowship co-Financed by European Union within European Social Fund for Young Scientists Młoda Kadra 2015 Plus 2013/2014 (III edycja)
  4. Fellowship co-Financed by European Union within European Social Fund for Young Scientists Młoda Kadra 2013
  5. Fellowship co-Financed by European Union within European Social Fund for Young Scientists Młoda Kadra 2012
  6. Rector Award for scientific achievements in the academic year 2011/2012
  7. Rector Award for scientific achievements in the academic year 2010/2011
  8. "Best Poster/Demo/Paper Award" at the conference SocInfo 2011 for the article "Tracking Group Evolution in Social Networks". Photos 1, 2 and 3 from the award ceremony.
  9. The winner of "Student Travel Suport" at the conference SocInfo 2011 for the article "Tracking Group Evolution in Social Networks". Photo from the award ceremony.
  10. Four time winner of the competition for Young Scientists to fund research aimed at developing young scientists and PhD students, organized by the Intitute of Informatics, Wrocław University of Technology
  11. Wroclaw City Council Scholarship 2011/2012
  12. Scholarship under the Przedsiębiorczy doktorant - inwestycja w innowacyjny rozwój regionu, funded by the Lower Silesian Marshal's Office and the European Union under the European Social Fund.
  13. Scholarship from the Wrocław University of Technology winter term 2011/2012
  14. Scholarship from the Wrocław University of Technology summer term 2010/2011
  15. PhD scholarship in 2008/2009, 2009/2010, 2010/2011 and 2011/2012
  16. Scholarship for outstanding achievement in science in 2004/2005, 2005/2006, 2006/2007, 2007/2008, 2008/2009, 2010/2011 and 2011/2012
  1. MultiSpred - Spread of influence in multilayer networks, research project funded by Polish National Science Centre, 2017-20, Project Manager and Participal Investigator.
  2. RENOIR - Reverse EngiNeering of sOcial Information pRocessing, H2020-MSCA-RISE-2015, 2016-19, no. 691152.
  3. Business Intelligence Tools for Virtual Sales Points, INNOTECH-K3/IN3/56/225874/NCBR/15, In-Tech, National Centre for Research and Development

  4. ENGINE - European research centre of Network intelliGence for INnovation Enhancement, FP7-REGPOT-2012-2013-1, 2013-16, no. 316097, Project Manager.
  5. Machine learning methods for complex networks, research project funded by Polish National Science Centre, 2014-17.
  6. Big data in banking - Assessment of different financial behaviour models, Alior Bank, 2013.
  7. Preparation and delivery of algorithms and mathematical models for xDSL services pre-qualification, Orange Labs, 2012-13.

  8. TRANSFoRm - Translational Research and Patient Safety in Europe ICT-2011.11.3, FP7, 2011-15.
  9. Przedsiębiorczy doktorant - inwestycja w innowacyjny rozwój regionu - Fellowship co-financed by European Union within European Social Fund - Project performed in cooperation with REC Global
  10. Data mining in complex social network systems, The Polish Ministry of Science and Higher Education research grant, 2010-13, in co-operation with Poznan University of Technology and AGH University of Science and Technology.
  11. GRASP# - Groups, Relationships and Activities of Suspected Persons, R&D Project founded by National Centre for Research and Development, in co-operation with Research & Engineering Center REC and Telnet, 2009-11
  12. MATURE - Continuous social learning in knowledge networks, Integrated Project no. 216356, 7FP ICT-2007.4.1, 2008-2012, Associated Partner.
  13. SoDiG - Social Values in Dynamic Groups, in co-operation with British Telecom, Intelligent Systems Research Centre (ISRC), 2008-09.

mLFR Benchamark

Testing Community Detection Algorithms in Multi–layered, Multiplex and Multiple Social Networks

This is the extention of LFR Benchmark introduced by A. Lancichinetti, S. Fortunato, F. Radicchi
in the paper Benchmark graphs for testing community detection algorithms. Community detection is one of the hottest topics in network science. While for simple (one layered) social networks there is hundreds of different algorithms for multilayer social networks there is a few. While for simple (one layered) social networks there is a number of reference dataset like karate club or football league, and few widely accepted and well tested benchmarks like GN Benchmark or LFR Benchmark for multilayer social networks there is a none. This paper propose an extension of well-known LFR Benchmark which will enable researchers to test and compare community detection algorithms in multilayer, multiplex and multiple social networks.

  1. Bródka P. A Method for GroupExtraction and Analysis in Multi-layered Social Networks Ph.D. disertation, Wrocław, Poland, 2012
    arXiv.org:1302.1369

  2. Bródka P., Grecki T.: mLFR Benchamark: Testing Community Detection Algorithms in Multilayer, Multiplex and Multiple Social Networks.

If you are using our mLFR Benchmark please cite our work and work of A. Lancichinetti, S. Fortunato and F. Radicchi

 Java application (jar)

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GED

The Method for Group Evolution Discovery in Social Networks

The continuous interest in the social network area contributes to the fast development of this field. The new possibilities of obtaining and storing data facilitate deeper analysis of the entire network, extracted social group and single individuals as well. One of the most interesting research topic is the dynamics of social group, it means analysis of Group Evolution over time. Having appropriate knowledge and methods for dynamic analysis, one may attempt to predict the future of the group and then manage it properly in order to achieve or change this predicted future according to specific needs. Such ability would be a powerful tool in the hands of human resource managers, personnel recruitment, marketing, etc.

The social Group Evolution consists of individual events and seven types of such changes have been identified in the paper: continuing, shrinking, growing, splitting, merging, dissolving and forming. To enable the analysis of Group Evolution a change indicator – inclusion measure was proposed. It has been used in a new method for exploring the evolution of social group, called Group Evolution Discovery (GED).

Introduction to the GED Method the poster or/and the presentation.

  1. Bródka P., Saganowski S., Kazienko P.: GED: The Method for Group Evolution Discovery in Social Networks, Social Network Analysis and Mining, March 2013, Volume 3, Issue 1, pp 1-14, DOI:10.1007/s13278-012-0058-8

  2. Saganowski S., Bródka P., Kazienko P.: Influence of the User Importance Measure on the Group Evolution Discovery Foundations of Computing and Decision Sciences, Volume 37, Issue 4, Pages 293-303, 2012

  3. Saganowski S., Bródka P., Kazienko P.: Influence of the Dynamic Social Network Timeframe Type and Size on the Group Evolution Discovery ASONAM 2012, IEEE Computer Society, 2012, pp. 678-682.

  4. Bródka P., Kazienko P, Kołoszczyk B.: Predicting Group Evolution in the Social Network SocInfo 2012, LNCS 7710, pp. 54–67, 2012.

The MS SQL Script with GED method - V_0.1

  1. Split your social network into timeframes
  2. For each timeframe calculate the communities (extract groups) using any group detection method. The GED method was tested for Clique Percolation Method and The Louvain Method
  3. For each group and each timeframe calculate the user importance measure e.g. degree centrality, betweenness centrality, closeness centrality, page rank, social position, etc.
  4. Create a new database in Microsoft SQL Server, download and run the SQL script
  5. Import your data into Groups_with_importance_measure table
  6. Execute the GED procedure e.g. EXEC [dbo].[GED]
  7. The results can be found in GED_evolution table
  8. Analyse and enjoy :)

GED implementationin Python by Diakidis, Georgios, et al. who used GED in the article Predicting the evolution of communities in social networks Proceedings of the 5th International Conference on Web Intelligence, Mining and Semantics. ACM, 2015.

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