URLs

• https://www.machinelearningplus.com/plots/top-50-matplotlib-visualizations-the-master-plots-python/?utm_medium=email&utm_source=topic+optin&utm_campaign=awareness&utm_content=20181219_data_nl&mkt_tok=eyJpIjoiWWpSbFpqVTBaamswTnpaaiIsInQiOiIwaGhtODhvbEhSZ1wvZWd2eWdKSlc2cUV3NnlNMXFMUTgySU5RZGRZRFk3WTBLcVRCUmJjT29cL1hWT2dVUHBFMjZkN0UzXC9lUWZvUmtkZGh1dzIrbW40R3RKUmJ0SDZGT1FZWnJ0RDRCK0tTdTVtUVNtTkZLZHlCQThRdUllVWtzaCJ9
• https://www.machinelearningplus.com/plots/top-50-matplotlib-visualizations-the-master-plots-python/

• http://sbp-conference.org/challenge/
• http://gdelt.utdallas.edu/
• http://cnets.indiana.edu/groups/nan/webtraffic/websci14-data
• http://www.europeansocialsurvey.org/
• http://en.wikipedia.org/wiki/Eurovision_Song_Contest_2011

The many facets of community detection in complex networks Schaub, M.T., Delvenne, JC., Rosvall, M. et al. Appl Netw Sci (2017) 2: 4. doi:10.1007/s41109-017-0023-6 (downloaded → bm)

• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4814833/
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4814833/pdf/srep23194.pdf
• http://www.nature.com/articles/ncomms5630
• http://rsif.royalsocietypublishing.org/content/11/101/20140940
• https://link.springer.com/article/10.1007/s41109-017-0023-6
• http://www.mapequation.org/assets/publications/mapequationtutorial.pdf

Zapiski

• http://www.karaoke.ru/artists/trio-marenichi/text/nese-galya-vodu/
• http://lyricstranslate.com/ru/%D0%BD%D0%B5%D1%81%D0%B5-%D0%B3%D0%B0%D0%BB%D1%8F-%D0%B2%D0%BE%D0%B4%D1%83-%D0%BD%D0%B5%D1%81%D0%B5%D1%82-%D0%B3%D0%B0%D0%BB%D1%8F-%D0%B2%D0%BE%D0%B4%D1%83.html
• https://kivy.org/#home
• http://www.educa.fmf.uni-lj.si/www375.zip
• http://www.stats.ox.ac.uk/~snijders/Trans_Triads_ha.pdf
• https://papers.ssrn.com/sol3/papers.cfm?abstract_id=259354
• https://en.wikipedia.org/wiki/Generalized_inverse_Gaussian_distribution
• https://en.wikipedia.org/wiki/Probability_distribution
• http://mivia.unisa.it/datasets/graph-database/vf3-library/
• https://www.facebook.com/TED/videos/10160380570415652/
• https://www.datasciencecentral.com/profiles/blogs/so-97-of-countries-have-open-data-but-is-that-the-whole-story
• https://www.datasciencecentral.com/profiles/blogs/the-word2vec-algorithm
• https://www.datasciencecentral.com/profiles/blogs/ai-deep-learning-explained-simply
• https://towardsdatascience.com/master-python-through-building-real-world-applications-part-1-b040b2b7faad

The SAGE Handbook of Social Network Analysis edited by: John Scott, Peter J. Carrington Chapter 3: L. Freeman: The development of SNA - with an Emphasis on recent events

Mixed Methods Social Networks Research: Design and Applications eds: Silvia Domínguez, Betina Hollstein page 57

https://jimis.episciences.org/3136/pdf https://arxiv.org/pdf/1707.07526