Skip to main content
SpringerLink
Log in

QAP Analysis of Company Co-mention Network

  • Conference paper
  • First Online:
Algorithms and Models for the Web Graph (WAW 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10836))

Included in the following conference series:

Abstract

In our research we form a network called company co-mention network. News analytics data have been employed to collect the companies co-mentioning. Each company acquires a certain value based on the amount of news in which the company was mentioned. A matrix containing the number of co-mentioning news between pairs of companies has been created for network analysis. Each company is presented as a node, and news mentioning two companies establishes a link between them. The network is constructed quite similarly to social networks or co-citation networks. The networked map of the companies is used to visualize the dependence structure of the economy by identifying groups of companies that are more central than others. The analysis carried out in the context of sectors of economy and territorial affiliation made it possible to identify key companies and to explore the similarity of the power law of vertices within sectors. QAP analysis between the co-mention network and the sector affiliation network was carried out to examine the ability of the sector affiliation network to predict the structure of the co-mention network.

This work was supported by the Russian Fund for Basic Research, project 18-37-00060.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Abbasi, A., Altmann, J.: On the correlation between research performance and social network analysis measures applied to research collaboration networks. In: 44th Hawaii International Conference on System Sciences (HICSS), pp. 1–10. IEEE (2011)

    Google Scholar 

  2. Albert, R., Barabasi, A.L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47–97 (2002)

    Article  MathSciNet  Google Scholar 

  3. An, J., Kwak, H.: What gets media attention and how media attention evolves over time: large-scale empirical evidence from 196 countries. In: Proceedings of the Eleventh International Conference on Web and Social Media, pp. 464–467. The AAAI Press, Palo Alto, Montreal, May 2017

    Google Scholar 

  4. Anthonisse, J.M.: The rush in a directed graph. Technical (1971)

    Google Scholar 

  5. Atzmueller, M., Schmidt, A., Kloepper, B., Arnu, D.: HypGraphs: an approach for analysis and assessment of graph-based and sequential hypotheses. In: Appice, A., Ceci, M., Loglisci, C., Masciari, E., Raś, Z.W. (eds.) NFMCP 2016. LNCS (LNAI), vol. 10312, pp. 231–247. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61461-8_15

    Chapter  Google Scholar 

  6. Barnett, G.: A longitudinal analysis of the international telecommunication network, 1978–1996. Am. Behav. Sci. 44, 1638–1655 (2001)

    Article  Google Scholar 

  7. Barnett, G., Danowski, J.: The structure of communication: a network analysis of the international communication association. Hum. Commun. Res. 19(2), 264–285 (1992)

    Article  Google Scholar 

  8. Barnett, G., Salisbury, J.: Communication and globalization: a longitudinal analysis of the international telecommunication network. J. World Syst. Res. 2(16), 1–17 (1996)

    Google Scholar 

  9. Basov, N., Lee, J.S., Antoniuk, A.: Social networks and construction of culture: a socio-semantic analysis of art groups. In: Cherifi, H., Gaito, S., Quattrociocchi, W., Sala, A. (eds.) Complex Networks & Their Applications V. COMPLEX NETWORKS 2016, vol. 693, pp. 785–796. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-50901-3_62

    Chapter  Google Scholar 

  10. Choi, E., Lee, K.C.: Relationship between social network structure dynamics and innovation: micro-level analyses of virtual cross-functional teams in a multinational B2B firm. Comput. Hum. Behav. 65, 151–162 (2016)

    Article  Google Scholar 

  11. Coletto, M., Garimella, K., Gionis, A., Lucchese, C.: A motif-based approach for identifying controversy. In: Proceedings of the Eleventh International Conference on Web and Social Media, pp. 496–499. The AAAI Press, Palo Alto, Montreal, May 2017

    Google Scholar 

  12. Correa, C., Crnovrsanin, T., Ma, K.L.: Visual reasoning about social networks using centrality sensitivity. IEEE Trans. Vis. Comput. Graph. 18(1), 106–120 (2012)

    Article  Google Scholar 

  13. Dekker, D., Krackhardt, D., Snijders, T.A.B.: Sensitivity of MRQAP tests to collinearity and autocorrelation conditions. Psychometrika 72(4), 563–581 (2007)

    Article  MathSciNet  Google Scholar 

  14. Deville, P., Song, C., Eagle, N., Blondel, V.D., Barabási, A.L., Wang, D.: Scaling identity connects human mobility and social interactions. Proc. Nat. Acad. Sci. 113(26), 7047–7052 (2016). http://www.pnas.org/content/113/26/7047

    Article  Google Scholar 

  15. Granovetter, M.: The strength of weak ties. Am. J. Sociol. 78, 1360 (1973)

    Article  Google Scholar 

  16. Guelzim, N., Bottani, S., Bourgine, P., Kepes, F.: Topological and causal structure of the yeast transciptional network. Nat. Genet. 31, 60–63 (2002)

    Article  Google Scholar 

  17. Haishu, Q., Ying, L., Xin, O.: Industrial association, common information spill out and industry stock indexes co-movement. Syst. Eng. Theory Pract. 36(11), 2737 (2016)

    Google Scholar 

  18. Hubert, L.: Assignment Methods in Combinatorial Data Analysis. Dekker, New York (1987)

    MATH  Google Scholar 

  19. Jeong, H., Tombor, B., Albert, R., Oltvai, Z.N., Barabasi, A.L.: The large-scale organization of metabolic networks. Nature 407, 651–654 (2000)

    Article  Google Scholar 

  20. Kim, H., Barnett, G.A.: Social network analysis using author co-citation data. In: AMCIS 2008 Proceedings, Paper 172, pp. 1–9 (2008)

    Google Scholar 

  21. Krackardt, D.: Qap partialling as a test of spuriousness. Soc. Netw. 9(2), 171–186 (1987)

    Article  MathSciNet  Google Scholar 

  22. Landherr, A., Friedl, B., Heidemann, J.: A critical review of centrality measures in social networks. Bus. Inf. Syst. Eng. 2(6), 371–385 (2010)

    Article  Google Scholar 

  23. Le, H., Shafiq, Z., Srinivasan, P.: Scalable news slant measurement using twitter. In: Proceedings of the Eleventh International Conference on Web and Social Media, pp. 584–587. The AAAI Press, Palo Alto, Montreal, May 2017

    Google Scholar 

  24. Lee, T.I., Rinaldi, N.J., Robert, F., Odom, D.T., Bar-Joseph, Z., Gerber, G.K., Hannett, N.M., Harbison, C.T., Thompson, C.M., Simon, I., Zeitlinger, J., Jennings, E.G., Murray, H.L., Gordon, D.B., Ren, B., Wyrick, J.J., Tagne, J.B., Volkert, T.L., Fraenkel, E., Gifford, D.K., Young, R.A.: Transcriptional regulatory networks in saccharomyces cerevisiae. Science 298(5594), 799–804 (2002)

    Article  Google Scholar 

  25. Liu, B.: Web Data Mining. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-37882-2

    Book  MATH  Google Scholar 

  26. Liu, X., Bollen, J., Nelson, M.L., de Sompel, V.: Co-authorship networks in the digital library research community. Inf. Process. Manag. 41(6), 1462–1480 (2005)

    Article  Google Scholar 

  27. Mantel, N.: The detection of disease clustering and a generalized regression approach. Cancer Res. 27(2), 209–220 (1967)

    Google Scholar 

  28. Mitra, G., Mitra, L. (eds.): The Handbook of News Analytics in Finance. Wiley, Hoboken (2011)

    Google Scholar 

  29. Mitra, G., Yu, X. (eds.): Handbook of Sentiment Analysis in Finance (2016)

    Google Scholar 

  30. Onnela, J.P., Arbesman, S., Gonzalez, M.C., Barabasi, A.L., Christakis, N.A.: Geographic constraints on social network groups. PLoS ONE 6(4), 1–7 (2011). https://doi.org/10.1371/journal.pone.0016939

    Article  Google Scholar 

  31. Ravasz, R., Barabasi, A.L.: Hierarchical organization in complex networks. Phys. Rev. E 67, 026112 (2003)

    Article  Google Scholar 

  32. Ravasz, R., Somera, A.L., Mongru, D.A., Oltvai, Z.N., Barabasi, A.L.: Hierarchical organization of modularity in metabolic networks. Science 297, 1551–1555 (2002)

    Article  Google Scholar 

  33. Said, Y.H., Wegman, E., Sharabati, W.K., Rigsby, J.: Social networks of author-coauthor relationships. Comput. Stat. Data Anal. 52(4), 2177–2184 (2008)

    Article  MathSciNet  Google Scholar 

  34. Samoilenko, A., Karimi, F., Edler, D., Kunegis, J., Strohmaier, M.: Linguistic neighbourhoods: explaining cultural borders on wikipedia through multilingual co-editing activity. EPJ Data Sci. 5, 1–20 (2016)

    Article  Google Scholar 

  35. Sidorov, S.P., Faizliev, A.R., Balash, V.A., Gudkov, A.A., Chekmareva, A.Z., Anikin, P.K.: Company co-mention network analysis. Springer Proceedings in Mathematics and Statistics (2018, in press)

    Google Scholar 

  36. Sidorov, S., Faizliev, A., Balash, V.: Measuring long-range correlations in news flow intensity time series. Int. J. Mod. Phys. C 28(08), 1750103 (2017)

    Article  MathSciNet  Google Scholar 

  37. Sidorov, S., Faizliev, A., Balash, V.: Scale invariance of news flow intensity time series. Nonlinear Phenom. Complex Syst. 19(4), 368–377 (2016)

    MathSciNet  Google Scholar 

  38. Sidorov, S., Faizliev, A., Balash, V.: Fractality and multifractality analysis of news sentiments time series. IAENG Int. J. Appl. Math. 48(1), 90–97 (2018)

    Google Scholar 

  39. Sidorov, S., Faizliev, A., Balash, V., Korobov, E.: Long-range correlation analysis of economic news flow intensity. Phys. A 444, 205–212 (2016)

    Article  Google Scholar 

  40. Sinatra, R., Wang, D., Deville, P., Song, C., Barabási, A.L.: Quantifying the evolution of individual scientific impact. Science 354(6312), aaf5239 (2016). http://science.sciencemag.org/content/354/6312/aaf5239

    Article  Google Scholar 

  41. Tang, J., Zhang, D., Yao, L.: Social network extraction of academic researchers. In: Seventh IEEE International Conference on Data Mining, pp. 292–301. IEEE (2007)

    Google Scholar 

  42. Vahtera, P., Buckley, P.J., Aliyev, M., Clegg, J., Cross, A.R.: Influence of social identity on negative perceptions in global virtual teams. J. Int. Manag. 23(4), 367–381 (2017)

    Article  Google Scholar 

  43. Wagner, A., Fell, D.A.: The small world inside large metabolic networks. Proc. R. Soc. Lond. B Biol. Sci. 268, 1803–1810 (2001)

    Article  Google Scholar 

  44. Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge (1994)

    Book  Google Scholar 

  45. West, R., Pfeffer, J.: Armed conflicts in online news: a multilingual study. In: Proceedings of the Eleventh International Conference on Web and Social Media, pp. 309–318. The AAAI Press, Palo Alto, Montreal, May 2017

    Google Scholar 

  46. Yook, S.H., Oltvai, Z.N., Barabasi, A.L.: Functional and topological characterization of protein interaction networks. Proteomics 4, 928–942 (2004)

    Article  Google Scholar 

  47. Zhang, A., Culbertson, B., Paritosh, P.: Characterizing online communities using coarse discourse structures. In: Proceedings of the Eleventh International Conference on Web and Social Media, pp. 357–366. The AAAI Press, Palo Alto, Montreal, May 2017

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Saratov State University, Saratov, Russian Federation

    S. P. Sidorov, A. R. Faizliev, V. A. Balash, A. A. Gudkov, A. Z. Chekmareva, M. Levshunov & S. V. Mironov

Authors
  1. S. P. Sidorov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. R. Faizliev
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. V. A. Balash
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A. A. Gudkov
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. A. Z. Chekmareva
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. M. Levshunov
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. S. V. Mironov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to A. R. Faizliev .

Editor information

Editors and Affiliations

  1. Department of Mathematics, Ryerson University, Toronto, Ontario, Canada

    Anthony Bonato

  2. Department of Mathematics, Ryerson University, Toronto, Ontario, Canada

    Paweł Prałat

  3. Department of Discrete Mathematics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia

    Andrei Raigorodskii

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sidorov, S.P. et al. (2018). QAP Analysis of Company Co-mention Network. In: Bonato, A., Prałat, P., Raigorodskii, A. (eds) Algorithms and Models for the Web Graph. WAW 2018. Lecture Notes in Computer Science(), vol 10836. Springer, Cham. https://doi.org/10.1007/978-3-319-92871-5_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-92871-5_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-92870-8

  • Online ISBN: 978-3-319-92871-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation