Publications

Bibliography of work produced under TD1210
(journal articles, other publications and books, explicit acknowledgement to [TD1210], members of TD1210)

Albano, A., Guillaume, J., Heymann, S., & Grand, B. Le. (2013). A matter of time – intrinsic or extrinsic – for diffusion in evolving complex networks. In Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining – ASONAM ’13 (pp. 202–206). New York, New York, USA: ACM Press. doi:10.1145/2492517.2492634

Aste, T., Butler, P., & Di Matteo, T. (2013). Self-referential order. Philosophical Magazine, 93(31-33), 3983–3992. doi:10.1080/14786435.2013.835495

Ausloos, M. (2013). Econophysics: Comments on a few Applications, Successes, Methods, & Models. IIM Kozhikode Society & Management Review, 2(2), 101–115. General Finance. doi:10.1177/2277975213507832, Preprint:http://arxiv.org/abs/1309.1953 [TD1210]

Ausloos, M. (2014a). Binary Scientific Star Coauthors Core Size. Scientometrics, 99(2), 30. Physics and Society; Digital Libraries. doi:10.1007/s11192-014-1230-x, Preprint: 1401.4069 [TD1210]

Ausloos, M. (2014b). Zipf-Mandelbrot-Pareto model for co-authorship popularity. Scientometrics, Online Fir, 30. Physics and Society; Adaptation and Self-Organizing Systems. doi:10.1007/s11192-014-1302-y, Preprint: http://arxiv.org/abs/1404.0269 [TD1210]

Ausloos, M., & Petroni, F. (2014). Threshold Model for Triggered Avalanches on Networks. In F. Petroni, F. Prattico, & G. D’Amico (Eds.), Stock Markets: Emergence, Macroeconomic Factors and Recent Developments (pp. 83–101). Physics and Society; Adaptation and Self-Organizing Systems, New York: Nova Science Publishers. Preprint http://arxiv.org/abs/1401.4270 [TD1210]

Bar-Ilan, J. (2014). JASIST@Mendeley revisited (preprint http://dx.doi.org/10.6084/m9.figshare.1031681).

Bar-Ilan, J., & Aharony, N. (2014). Twelve years of Wikipedia research (p. Proceedings of the ACM WebSci 2014 Conference, Bloomington – to appear).

Chavalarias, D., & Cointet, J.-P. (2013). Phylomemetic patterns in science evolution–the rise and fall of scientific fields. PloS One, 8(2), e54847. doi:10.1371/journal.pone.0054847

Delanoë, A., & Galam, S. (2014). Modeling a controversy in the press: The case of abnormal bee deaths. Physica A: Statistical Mechanics and Its Applications, 402, 93–103. Physics and Society; Computation and Language. doi:10.1016/j.physa.2014.01.054 Preprint http://arxiv.org/pdf/1209.2163v1.pdf

Ferber, C., & Holovatch, Y. (2013). Fractal transit networks: Self-avoiding walks and Lévy flights. The European Physical Journal Special Topics, 216(1), 49–55. Physics and Society; Statistical Mechanics. doi:10.1140/epjst/e2013-01728-0, Preprint: http://arxiv.org/abs/1209.2590

Firmino, H., & Baptista, A. (2013). Making sense of a flat list of terms into Linked Open Data SKOS vocabularies. In N. Lavesson (Ed.), Mining the Digital Information Networks (pp. 89–89). IOS Press. Retrieved from http://iospress.metapress.com/index/04227402576TP123.pdf

Frittelli, M., & Peri, I. (2014). Scientific Research Measures. Working paper  (p. 47). PDF available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2287672&download=yes

Galam, S. (2013). Modeling the Forming of Public Opinion: An approach from Sociophysics. Global Economics and Management Review, 18(1), 2–11. doi:10.1016/S2340-1540(13)70002-1

Galina, V., & Galam, S. (2014). Dissolution of a Global Alliance: War or Peace Vinogradova Galina, Serge Galam. Policy Studies Organization, 1(1), 93–107. PDF here

Garas, A., Tomasello, M. V, & Schweitzer, F. (2014). Selection rules in alliance formation: strategic decisions or abundance of choice?, 15. Physics and Society. Retrieved from http://arxiv.org/abs/1403.3298

Garcia, D., Mavrodiev, P., & Schweitzer, F. (2013). Social resilience in online communities. In Proceedings of the first ACM conference on Online social networks – COSN ’13 (pp. 39–50). Physics and Society, New York, New York, USA: ACM Press. doi:10.1145/2512938.2512946

Gramatica, R., Di Matteo, T., Giorgetti, S., Barbiani, M., Bevec, D., & Aste, T. (2014). Graph theory enables drug repurposing–how a mathematical model can drive the discovery of hidden mechanisms of action. PloS One, 9(1), e84912. doi:10.1371/journal.pone.0084912 [TD1210]

Heymann, S. (2014). Exploratory Link Stream Analysis for Event Detection. PhD Thesis l’UNIVERSITÉ PIERRE ET MARIE CURIE. Retrieved from http://tel.archives-ouvertes.fr/docs/00/99/47/66/PDF/these_archivage_3072427.pdf

Heymann, S. (2014). Gephi. In Encyclopedia of Social Networks and Mining (ESNAM). Springer International.

Heymann, S., & Grand, B. Le. (2013). Monitoring user-system interactions through graph-based intrinsic dynamics analysis. In IEEE 7th International Conference on Research Challenges in Information Science (RCIS) (pp. 1–10). IEEE. doi:10.1109/RCIS.2013.6577695

Heymann, S., & Le Grand, B. (2013). Towards a redefinition of time in information networks? In Proceedings of the 5th Annual ACM Web Science Conference on – WebSci ’13 (pp. 158–161). New York, New York, USA: ACM Press. doi:10.1145/2464464.2464498

Heymann, S., & Le Grand, B. (2014). Exploratory Network Analysis. In H. Cherifi (Ed.), Complex Networks and their Applications (p. to appear). Cambridge University Press.

Jacomy, M., Heymann, S., Venturini, T., & Bastian, M. (2014). ForceAtlas2 , A Continuous Graph Layout Algorithm for Handy Network Visualization (pp. 1–22 (to appear PlosOne)).

Lambiotte, R., Salnikov, V., & Rosvall, M. (2014). Effect of Memory on the Dynamics of Random Walks on Networks. arXiv Preprint arXiv:1401.0447, 1–6. Retrieved from http://arxiv.org/abs/1401.0447 [TD1210]

Lambiotte, R., Tabourier, L., & Delvenne, J.-C. (2013). Burstiness and spreading on temporal networks. The European Physical Journal B, 86, 320. doi:10.1140/epjb/e2013-40456-9 Preprint: http://arxiv.org/abs/1305.0543 [TD1210]

Leydesdorff, L., Carley, S., & Rafols, I. (2013). Global maps of science based on the new Web-of-Science categories. Scientometrics, 94(2), 589–593. doi:10.1007/s11192-012-0784-8 Preprint:http://arxiv.org/abs/1202.1914

Leydesdorff, L., Rafols, I., & Chen, C. (2013). Interactive Overlays of Journals and the Measurement of Interdisciplinarity on the basis of Aggregated Journal-Journal Citations. Journal of the American Society for Information Science and Technology, 64(12), 2573–2586. Digital Libraries. doi:10.1002/asi.22946, Preprint: http://arxiv.org/abs/1301.1013

Malta, M. C., & Baptista, A. A. (2013a). A Method for the Development of Dublin Core Application Profiles (Me4DCAP V0.2): Detailed Description. In Proc. Int’l Conference on Dublin Core and Metadata Applications (pp. 90–103).

Malta, M. C., & Baptista, A. A. (2013b). Me4DCAP V0.1: A method for the development of Dublin Core Application Profiles. Information Services & Use, 33, 161–171. doi:10.3233/ISU-130706

Malta, M. C., & Baptista, A. A. (2013c). State of the art on methodologies for the development of a metadata application profile. International Journal of Metadata, Semantics and Ontologies, 8(4), 332. doi:10.1504/IJMSO.2013.058416

Malta, M. C., & Baptista, A. A. (2014). A panoramic view on metadata application profiles of the last decade. International Journal of Metadata, Semantics and Ontologies, 9(1), 58. doi:10.1504/IJMSO.2014.059124

Marx, W., Bornmann, L., Barth, A., & Leydesdorff, L. (2014). Detecting the historical roots of research fields by reference publication year spectroscopy (RPYS). Journal of the Association for Information Science and Technology, 65(4), 751–764. Digital Libraries; Computers and Society. doi:10.1002/asi.23089, Preprint: http://arxiv.org/abs/1309.5706

Mayr, P., Scharnhorst, A., Larsen, B., Schaer, P., & Mutschke, P. (2013). Bibliometric-enhanced Information Retrieval. In M. D. et al. Rijke (Ed.), 36th European Conference on IR Research, ECIR 2014, Amsterdam, The Netherlands, April 13-16, 2014. Proceedings (pp. 798–801). Information Retrieval; Digital Libraries; Physics and Society, Springer International. doi:10.1007/978-3-319-06028-6_99, Preprint: http://arxiv.org/abs/1310.8226

Morales, R., Di Matteo, T., & Aste, T. (2014). Dependency structure and scaling properties of financial time series are related. Scientific Reports, 4, 4589. doi:10.1038/srep04589, [TD1210]

Morales, R., Di Matteo, T., & Aste, T. (2013). Non-stationary multifractality in stock returns. Physica A: Statistical Mechanics and Its Applications, 392(24), 6470–6483. doi:10.1016/j.physa.2013.08.037 [TD1210]

Mouakher, A., Heymann, S., Yahia, S. Ben, & Le Grand, B. (2013). Efficient Visualization of Folksonomies Based on «Intersectors». In H. L. Larsen, M. J. Martin-Bautista, M. A. Vila, T. Andreasen, & H. Christiansen (Eds.), Flexible Query Answering Systems. 10th International Conference, FQAS 2013, Granada, Spain, September 18-20, 2013. Proceedings (Lecture No., pp. 637–648). Springer International. doi:10.1007/978-3-642-40769-7_55

Mryglod, O., Kenna, R., Holovatch, Y., & B. Berche. (2014). On the comparison of extensive and intensive measures of scientific group efficiency. Rep. Nat. Acad. Sci. of Ukraine, (to appear). PDF here

Mryglod, O., Kenna, R., Holovatch, Y., & Berche, B. (2012). Absolute and specific measures of research group excellence. Scientometrics, 95(1), 115–127. Applications; Digital Libraries; Physics and Society. doi:10.1007/s11192-012-0874-7, Preprint: http://arxiv.org/abs/1210.0732

Mryglod, O., Kenna, R., Holovatch, Y., & Berche, B. (2013a). Comparison of a citation-based indicator and peer review for absolute and specific measures of research-group excellence. Scientometrics, 97(3), 767–777. Digital Libraries; Physics and Society. doi:10.1007/s11192-013-1058-9, Preprint: http://arxiv.org/abs/1305.6256

Mryglod, O., Kenna, R., Holovatch, Y., & Berche, B. (2013b). On the problem of science evaluation (in Ukrainian). Herald of the National Academy of Sciences of Ukraine, 76–85. PDF here

Osińska, V. (2014). Infovis Mechanisms in Information Architecture [in Polish: Rola mechanizmów wizualizacyjnych w architekturze informacji]. Toruńskie Studia Bibliologiczne, 6(2 (11)), 81. doi:10.12775/TSB.2013.023

Osinska, V., Dreszer-Drogorob, J., Osinski, G., & Gawarkiewicz, M. (2013). Cognitive Approach in Classification Visualization: end-users study. In A. Slavic, A. A. Salah, & S. Davies (Eds.), Classification and visualization: interfaces to knowledge (pp. 273–281). Würzburg: Ergon Verlag.

Osińska, V., & Komendziński, T. (2014). Scientists on Facebook. Visualization of social networks in science [in Polish: Naukowcy na facebook- u . Wizualizacja sieci społecznych w nauce]. In E. Glowacka (Ed.), Contemporary aspects of communication and information. Problems, research, hypothesis (pp. 269–282). Toruń: NCU Publishing 2014. Retrieved from http://repozytorium.umk.pl/bitstream/handle/item/1779/VOsinska_HomoCommunicativus.pdf?sequence=1

Pfitzner, R., Scholtes, I., Garas, A., Tessone, C. J., & Schweitzer, F. (2013). Betweenness Preference: Quantifying Correlations in the Topological Dynamics of Temporal Networks. Physical Review Letters, 110(19), 198701. doi:10.1103/PhysRevLett.110.198701

Pozzi, F., Di Matteo, T., & Aste, T. (2013). Spread of risk across financial markets: better to invest in the peripheries. Scientific Reports, 3, 1665. doi:10.1038/srep01665

Richmond, P., Sexton, M. B., Hardiman, S. J., & Hutzler, S. (2014). Generalised diffusion model of asset price fluctuations. The European Physical Journal B, 87(3), 63. doi:10.1140/epjb/e2014-40599-1

Rodrigues, E., Swan, A., & Baptista, A. A. (2013). Uma Década de Acesso Aberto na UMinho e no Mundo (p. 261). Braga, Portugal: Universidade do Minho, Serviços de Documentação.

Rosvall, M., Esquivel, A. V., Lancichinetti, A., West, J. D., & Lambiotte, R. (2013). Memory in network flows and its effects on community detection, ranking, and spreading. ArXiv, 25. Physics and Society. Retrieved from http://arxiv.org/abs/1305.4807

Rotundo, G. (2014). Black–Scholes–Schrödinger–Zipf–Mandelbrot model framework for improving a study of the coauthor core score. Physica A: Statistical Mechanics and Its Applications, 404, 296–301. doi:10.1016/j.physa.2014.02.011

Rotundo, G., & Ausloos, M. (2013). Complex-valued information entropy measure for networks with directed links (digraphs). Application to citations by community agents with opposite opinions. The European Physical Journal B, 86(4), 169. doi:10.1140/epjb/e2013-30985-6

Sarigöl, E., Pfitzner, R., Scholtes, I., Garas, A., & Schweitzer, F. (2014). Predicting Scientific Success Based on Coauthorship Networks, 21. Physics and Society; Digital Libraries. Retrieved from http://arxiv.org/abs/1402.7268

Scholtes, I., Pfitzner, R., & Schweitzer, F. (2014). The Social Dimension of Information Ranking: A Discussion of Research Challenges and Approaches. In Social Informatics – The Social Impact of Interactions between Humans and IT (p. to appear).

Scholtes, I., Wider, N., Pfitzner, R., Garas, A., Tessone, C. J., & Schweitzer, F. (2013). Slow-Down vs. Speed-Up of Diffusion in Non-Markovian Temporal Networks, (iii), 20. Physics and Society; Disordered Systems and Neural Networks; Statistical Mechanics. Retrieved from http://arxiv.org/abs/1307.4030

Slavic, A., Akdag Salah, A., & Davies, S. (Eds.). (2013). Classification & visualization: Interfaces to knowledge ; proceedings of the International UDC Seminar 24 – 25 October 2013. Würzburg: Ergon Verlag. Retrieved from http://www.udcc.org/index.php/site/page?view=visualization

Tadic, B., Gligorijevic, V., Skowron, M., & Suvakov, M. (2014). The dynamics of emotional chats with Bots: Experiment and agent-based simulations. ScienceJet, 3, 50. Retrieved from http://www.cognizure.com/sj.aspx?p=200638376 [TD1210]

Tadić, B., & Šuvakov, M. (2013). Can human-like Bots control collective mood: agent-based simulations of online chats. Journal of Statistical Mechanics: Theory and Experiment, 2013(10), P10014. doi:10.1088/1742-5468/2013/10/P10014 [TD1210]

Tomasello, M. V., Napoletano, M., Garas, A., & Schweitzer, F. (2013). The Rise and Fall of R&D Networks. Arxiv Preprint 1304.3623, 34. Physics and Society. Retrieved from http://arxiv.org/abs/1304.3623

Tomasello, M. V., Perra, N., Tessone, C. J., Karsai, M., & Schweitzer, F. (2014). The role of endogenous and exogenous mechanisms in the formation of R&D networks. Physics and Society; Data Analysis, Statistics and Probability. Retrieved from http://arxiv.org/abs/1403.4106

Uboldi, G., Caviglia, G., Coleman, N., Heymann, S., Mantegari, G., & Ciuccarelli, P. (2013). Knot: an Interface for the Study of Social Networks in the Humanities Giorgio. In Proceedings of the Biannual Conference of the Italian Chapter of SIGCHI on – CHItaly ’13 (pp. 1–9). New York, New York, USA: ACM Press. doi:10.1145/2499149.2499174

Van Hoek, W., Shen, W., & Mayr, P. (2014). Identifying User Behavior in domain-specific Repositories. Arxiv Digital Libraries (cs.DL); 1403.7899, Elpub Conference 2014, 10. Digital Libraries; Information Retrieval. Retrieved from http://arxiv.org/abs/1403.7899

Vitanov, N. K., Dimitrova, Z. I., & Vitanov, K. N. (2014). Science dynamics and scientific productivity. Sofia: Publishing House ´Vanio Nedkov.

Zanetti, M. S., Scholtes, I., Tessone, C. J., & Schweitzer, F. (2013a). Categorizing Bugs with Social Networks: A Case Study on Four Open Source Software Communities. In ICSE ’13 Proceedings of the 2013 International Conference on Software Engineering (pp. 1032–1041). Retrieved from http://arxiv.org/abs/1302.6764

Zanetti, M. S., Scholtes, I., Tessone, C. J., & Schweitzer, F. (2013b). The rise and fall of a central contributor: Dynamics of social organization and performance in the GENTOO community. In 2013 6th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE) (pp. 49–56). IEEE. doi:10.1109/CHASE.2013.6614731

 

KnoweScape also maintains a Mendeley group with a collection of literature relevant for Knowledge Maps (including TD1210 work) See http://www.mendeley.com/groups/1581483/knowescape-the-dynamics-of-information-and-knowledge-landscapes/

 

To the TD1210 members

Please acknowledge each publication funded under KnowEscape with the following sentence: The work [or: part of this work] has been funded by the COST Action TD1210 KnowEscape!