Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Motion-Specialized Deep Convolutional Descriptor for Plant Water Stress Estimation Read chapter Read first chapter

2017 | OriginalPaper | Chapter

A Genetic Algorithm for Discovering Linguistic Communities in Spatiosocial Tensors with an Application to Trilingual Luxemburg

Authors : Georgios Drakopoulos, Fotini Stathopoulou, Giannis Tzimas, Michael Paraskevas, Phivos Mylonas, Spyros Sioutas

Published in: Engineering Applications of Neural Networks

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Multimodal social networks are omnipresent in Web 2.0 with virtually every human communication action taking place there. Nonetheless, language remains by far the main premise such communicative acts unfold upon. Thus, it is statutory to discover language communities especially in social data stemming from historically multilingual countries such as Luxemburg. An adjacency tensor is especially suitable for representing such spatiosocial data. However, because of its potentially large size, heuristics should be developed for locating community structure efficiently. Linguistic structure discovery has a plethora of applications including digital marketing and online political campaigns, especially in case of prolonged and intense cross-linguistic contact. This conference paper presents TENSOR-G, a flexible genetic algorithm for approximate tensor clustering along with two alternative fitness functions derived from language variation or diffusion properties. The Kruskal tensor decomposition serves as a benchmark and the results obtained from a set of trilingual Luxemburgian tweets are analyzed with linguistic criteria.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Efficient Computation of Palindromes in Sequences with Uncertainties
next chapter Analyzing the Mobile Learning System Behavior: The Case of the Russian Verbs of Motion
Footnotes
Literature
1.
Androutsopoulos, J.: Language change and digital media: a review of conceptions and evidence. In: Standard Languages and Language Standards in a Changing Europe (2011)
2.
Backstrom, L., Sun, E., Marlow, C.: Find me if you can: improving geographical prediction with social and spatial proximity. In: Proceedings of the 19th International Conference on World Wide Web, pp. 61–70. ACM (2010)
3.
Bader, B.W., Kolda, T.G.: Efficient MATLAB computations with sparse and factored tensors. SIAM J. Sci. Comput. 30(1), 205–231 (2007)MathSciNetCrossRefMATH
4.
Bader, B.W., Kolda, T.G., et al.: MATLAB tensor toolbox version 2.5 (2012)
5.
Booker, L.B., Goldberg, D.E., Holland, J.H.: Classifier systems and genetic algorithms. Artif. Intell. 40(1–3), 235–282 (1989)CrossRef
6.
Cardoso, J.F.: Eigen-structure of the fourth-order cumulant tensor with application to the blind source separation problem. In: ICASSP-90, pp. 2655–2658. IEEE (1990)
7.
Croft, W.: Mixed languages and acts of identity: an evolutionary approach. Mixed Lang. Debate: Theoret. Empirical Adv. 145, 41 (2003)
8.
Darwin, C.: On the origin of species by means of natural selection. John Murray, November 1859
9.
Dawkins, R.: The Selfish Gene, 30th edn. Oxford University Press, Oxford (2006)
10.
De Jong, K.: Learning with genetic algorithms: an overview. Mach. Learn. 3(2), 121–138 (1988)
11.
De Lathauwer, L., Vandewalle, J.: Dimensionality reduction in higher-order signal processing and rank-\((r_1, r_2, \ldots, r_n)\) reduction in multilinear algebra. LAA 391, 31–55 (2004)MathSciNetMATH
12.
Dixon, R.M.: The Rise and Fall of Languages. Cambridge University Press, Cambridge (1997)
13.
14.
Drakopoulos, G.: Tensor fusion of social structural and functional analytics over Neo4j. In: Proceedings of the 6th International Conference of Information, Intelligence, Systems, and Applications, IISA 2016. IEEE, July 2016
15.
Drakopoulos, G., Kanavos, A.: Tensor-based document retrieval over Neo4j with an application to PubMed mining. In: Proceedings of the 6th International Conference of Information, Intelligence, Systems, and Applications, IISA 2016. IEEE, July 2016
16.
Drakopoulos, G., Kanavos, A., Karydis, I., Sioutas, S., Vrahatis, A.G.: Tensor-based semantically-enhanced PubMed retrieval. Computation, May 2017. Accepted
17.
Drakopoulos, G., Megalooikonomou, V.: An adaptive higher order scheduling policy with an application to biosignal processing. In: SSCI 2016. IEEE, December 2016
18.
Dunlavy, D.M., Kolda, T.G., Acar, E.: Temporal link prediction using matrix and tensor factorizations. TKDD 5(2), 10 (2011)CrossRef
19.
Eisenstein, J.: Sociolinguistic variation in online social media. In: 2015 AAAS Annual Meeting (2015)
20.
Eisenstein, J., O’Connor, B., Smith, N.A., Xing, E.P.: Diffusion of lexical change in social media. PLoS One 9(11) (2014)
21.
Eleta, I., Golbeck, J.: Bridging languages in social networks: how multilingual users of Twitter connect language communities? Proc. Am. Soc. Inf. Sci. Technol. 49(1), 1–4 (2012)CrossRef
22.
Ge, X., Cheng, H., Guizani, M., Han, T.: 5G wireless backhaul networks: challenges and research advances. IEEE Netw. 28(6), 6–11 (2014)CrossRef
23.
Goel, R., Soni, S., Goyal, N., Paparrizos, J., Wallach, H., Diaz, F., Eisenstein, J.: The social dynamics of language change in online networks. In: Spiro, E., Ahn, Y.-Y. (eds.) SocInfo 2016. LNCS, vol. 10046, pp. 41–57. Springer, Cham (2016). doi:10.​1007/​978-3-319-47880-7_​3 CrossRef
24.
Goldberg, D.E., Holland, J.H.: Genetic algorithms and machine learning. Mach. Learn. 3(2), 95–99 (1988)CrossRef
25.
Hale, M.: Historical Linguistics: Theory and Method. Wiley-Blackwell, Hoboken (2007)
26.
Hale, S.A.: Global connectivity and multilinguals in the Twitter network. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 833–842. ACM (2014)
27.
Hong, L., Convertino, G., Chi, E.H.: Language matters in Twitter: a large scale study. In: ICWSM (2011)
28.
Kershaw, D., Rowe, M., Noulas, A., Stacey, P.: Birds of a feather talk together: user influence on language adoption. In: Proceedings of the 50th Hawaii International Conference on System Sciences (2017)
29.
Kershaw, D., Rowe, M., Stacey, P.: Language innovation and change in on-line social networks. In: Proceedings of the 26th ACM Conference on Hypertext and Social Media, pp. 311–314. ACM (2015)
30.
Kirk, N.A., Mees, B.: Stalin, Marr and the struggle for a Soviet linguistics. Verbatim 31(3) (2006)
31.
32.
Kontopoulos, S., Drakopoulos, G.: A space efficient scheme for graph representation. In: Proceedings of the 26th International Conference on Tools with Artificial Intelligence, ICTAI 2014, pp. 299–303. IEEE, November 2014
33.
Labov, W.: Principles of linguistic change vol. 2: social factors. Lang. Soc. 29 (2001)
34.
35.
Matras, Y.: Languages in contact in a world marked by change and mobility. Revue française de linguistique appliquée 18(2), 7–13 (2013)
36.
Matsumoto, K.: The role of social networks in the post-colonial multilingual island of Palau: mechanisms of language maintenance and shift. Multilingua-J. Cross-Cultural Interlang. Commun. 29(2), 133–165 (2010)MathSciNetCrossRef
37.
Maybaum, R.: Language change as a social process: diffusion patterns of lexical innovations in Twitter. In: Annual Meeting of the Berkeley Linguistics Society, pp. 152–166 (2013)
38.
Michael, L., Bowern, C., Evans, B.: Social dimensions of language change. In: Bowern, C., Evans, B. (eds.) Routledge Handbook of Historical Linguistics, pp. 484–502. Routledge (2014)
39.
Milroy, J., Milroy, L.: Linguistic change, social network and speaker innovation. J. Linguist. 21(02), 339–384 (1985)CrossRef
40.
Milroy, L.: Language and Social Networks, 2nd edn. Blackwell, Oxford (1980)
41.
Nevalainen, T.: Social networks and language change in Tudor and Stuart London-only connect? English Lang. Linguist. 19(2), 269–292 (2015)CrossRef
42.
Nion, D., Sidiropoulos, N.D.: Tensor algebra and multidimensional harmonic retrieval in signal processing for MIMO radar. IEEE Trans. Sig. Process. 58(11), 5693–5705 (2010)MathSciNetCrossRef
43.
Pakendorf, B.: Historical linguistics and molecular anthropology. In: Bowern, C., Evans, B. (eds.) Routledge Handbook of Historical Linguistics. Routledge (2014)
44.
Papalexakis, E., Doğruöz, A.S.: Understanding multilingual social networks in online immigrant communities. In: 24th WWW, pp. 865–870. ACM (2015)
45.
Stalin, J.V.: Marxism and problems of linguistics. In: Pravda, May 1950
46.
Tagkalakis, F., Papagiannaki, A., Drakopoulos, G., Megalooikonomou, V.: Augmenting fMRI-generated brain connectivity with temporal information. In: Proceedings of the 6th International Conference of Information, Intelligence, Systems, and Applications, IISA 2016. IEEE, July 2016
47.
Trudgill, P.: Social structure, language contact and language change. In: The SAGE Handbook of Sociolinguistics, pp. 236–249 (2011)
48.
Weinreich, U., Labov, W., Herzog, M.I.: Empirical foundations for a theory of language change. University of Texas Press, Austin (1968)
49.
Westin, C.F., Maier, S.E., Mamata, H., Nabavi, A., Jolesz, F.A., Kikinis, R.: Processing and visualization for diffusion tensor MRI. Med. Image Anal. 6(2), 93–108 (2002)CrossRef
Metadata
Title
A Genetic Algorithm for Discovering Linguistic Communities in Spatiosocial Tensors with an Application to Trilingual Luxemburg
Authors
Georgios Drakopoulos
Fotini Stathopoulou
Giannis Tzimas
Michael Paraskevas
Phivos Mylonas
Spyros Sioutas
Copyright Year
2017
Book
Engineering Applications of Neural Networks

Print ISBN: 978-3-319-65171-2

Electronic ISBN: 978-3-319-65172-9

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-65172-9_53

Premium Partner

    Image Credits