Skip to main content
Top
Published in: Information Systems Frontiers 1/2017

26-09-2015

Extracting the patterns of truthfulness from political information systems in Serbia

Author: Nenad Tomašev

Published in: Information Systems Frontiers | Issue 1/2017

Log in

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

search-config
loading …

Abstract

In modern information societies, there are information systems that track and log parts of the ongoing political discourse. Due to the sheer volume of the accumulated data, automated tools are required in order to enable citizens to better interpret political statements and promises, as well as evaluate their truthfulness. We propose an approach to use the established machine learning and data mining techniques for analyzing annotated political statements and promises available via the Serbian Truth-o-meter (Istinomer) system in order to extract and interpret the hidden patterns of truthfulness and deceit. We perform standard textual processing and topic extraction and associate topical truthfulness profiles with the promise makers, for pattern discovery and prediction. Prevailing trends in Serbian political discourse emerge as strong association rules where truthfulness is set as the target variable. The evaluated set of standard content-based prediction models exhibit a bias towards the negative outcomes, due to an overall low truthfulness rate in the data. Our results demonstrate that it is possible to use data mining within political information systems for generating insights into the workings of governments.

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!

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!

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!

Literature
go back to reference Adamic, L., & Glance, N. (2005). The political blogosphere and the 2004 U.S. election: Divided they blog. In In LinkKDD’05: Proceedings of the 3rd international workshop on Link discovery (pp. 36–43). Adamic, L., & Glance, N. (2005). The political blogosphere and the 2004 U.S. election: Divided they blog. In In LinkKDD’05: Proceedings of the 3rd international workshop on Link discovery (pp. 36–43).
go back to reference Adamo, J. (2001). Data Mining for Association Rules and Sequential Patterns: Sequential and Parallel Algorithms. Berlin: Springer.CrossRef Adamo, J. (2001). Data Mining for Association Rules and Sequential Patterns: Sequential and Parallel Algorithms. Berlin: Springer.CrossRef
go back to reference Agirre, E., Martínez, D., de Lacalle, O.L., & Soroa, A (2006). Two graph-based algorithms for state-of-the-art WSD. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) (pp. 585–593). Agirre, E., Martínez, D., de Lacalle, O.L., & Soroa, A (2006). Two graph-based algorithms for state-of-the-art WSD. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) (pp. 585–593).
go back to reference Agrawal, R., Imieliński, T., & Swami, A. (1993). Mining association rules between sets of items in large databases. SIGMOD Rec, 22(2), 207–216.CrossRef Agrawal, R., Imieliński, T., & Swami, A. (1993). Mining association rules between sets of items in large databases. SIGMOD Rec, 22(2), 207–216.CrossRef
go back to reference AlSumait, L., Barbara, D., & Domeniconi, C. (2008). On-line LDA: Adaptive topic models for mining text streams with applications to topic detection and tracking. In Eighth IEEE International Conference on Data Mining (ICDM) (pp. 3–12). AlSumait, L., Barbara, D., & Domeniconi, C. (2008). On-line LDA: Adaptive topic models for mining text streams with applications to topic detection and tracking. In Eighth IEEE International Conference on Data Mining (ICDM) (pp. 3–12).
go back to reference Baccianella, A.E.S., Sebastiani, F., & Sentiwordnet 3.0 (2010). An enhanced lexical resource for sentiment analysis and opinion mining. In Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC’10). European Language Resources Association (ELRA), Valletta, Malta. Baccianella, A.E.S., Sebastiani, F., & Sentiwordnet 3.0 (2010). An enhanced lexical resource for sentiment analysis and opinion mining. In Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC’10). European Language Resources Association (ELRA), Valletta, Malta.
go back to reference Balasubramanyan, R., Routledge, B.R., & Smith, N.A. (2010). From tweets to polls : Linking text sentiment to public opinion time series. Balasubramanyan, R., Routledge, B.R., & Smith, N.A. (2010). From tweets to polls : Linking text sentiment to public opinion time series.
go back to reference Cagliero, L., & Fiori, A. (2013). Discovering generalized association rules from twitter. Intelligent Data Analysis, 17(4), 627–648. Cagliero, L., & Fiori, A. (2013). Discovering generalized association rules from twitter. Intelligent Data Analysis, 17(4), 627–648.
go back to reference Campbell, J.E. (2008). Evaluating u.s. presidential election forecasts and forecasting equations. Int. J. Forecast., 24(2), 259–271.CrossRef Campbell, J.E. (2008). Evaluating u.s. presidential election forecasts and forecasting equations. Int. J. Forecast., 24(2), 259–271.CrossRef
go back to reference Carruba, C., Gabel, M., Murrah, L., Clough, R., Montgomery, E., & Schambach, R. (2006). Off the Record: Unrecorded Legislative Votes, Selection Bias and Roll-Call Vote Analysis. Br. J. Polit. Sci., 36(4), 691–704.CrossRef Carruba, C., Gabel, M., Murrah, L., Clough, R., Montgomery, E., & Schambach, R. (2006). Off the Record: Unrecorded Legislative Votes, Selection Bias and Roll-Call Vote Analysis. Br. J. Polit. Sci., 36(4), 691–704.CrossRef
go back to reference Cavnar, W.B., & Trenkle, J.M. (1994). N-gram-based text categorization. In Proceedings of SDAIR-94, 3rd Annual Symposium on Document Analysis and Information Retrieval (pp. 161–175). Cavnar, W.B., & Trenkle, J.M. (1994). N-gram-based text categorization. In Proceedings of SDAIR-94, 3rd Annual Symposium on Document Analysis and Information Retrieval (pp. 161–175).
go back to reference Charalabidis, Y., & Koussouris, S. (Eds.) (2012). Empowering Open and Collaborative Governance - Technologies and Methods for Online Citizen Engagement in Public Policy Making. Springer Charalabidis, Y., & Koussouris, S. (Eds.) (2012). Empowering Open and Collaborative Governance - Technologies and Methods for Online Citizen Engagement in Public Policy Making. Springer
go back to reference Charalabidis, Y., Triantafillou, A., Karkaletsis, V., & Loukis, E. (2012). Public policy formulation through non moderated crowdsourcing in social media, (pp. 156–169): Springer. Charalabidis, Y., Triantafillou, A., Karkaletsis, V., & Loukis, E. (2012). Public policy formulation through non moderated crowdsourcing in social media, (pp. 156–169): Springer.
go back to reference Cliffe, L., Ramsay, M., & Bartlett, D. (2000). The politics of lying: Implications for democracy: St Martin’s Press. Cliffe, L., Ramsay, M., & Bartlett, D. (2000). The politics of lying: Implications for democracy: St Martin’s Press.
go back to reference Clinton, J., Jackman, S., & Douglas, R. (2004). The Statistical Analysis of Roll Call Data. Am. Polit. Sci. Rev., 2, 355–370.CrossRef Clinton, J., Jackman, S., & Douglas, R. (2004). The Statistical Analysis of Roll Call Data. Am. Polit. Sci. Rev., 2, 355–370.CrossRef
go back to reference Custers, H., Calders, T., & Zarsky, T. (2013). Discrimination and Privacy in the Information Society: Data Mining and Profiling in Large Databases. Studies in applied philosophy, epistemology and rational ethics: Springer. Custers, H., Calders, T., & Zarsky, T. (2013). Discrimination and Privacy in the Information Society: Data Mining and Profiling in Large Databases. Studies in applied philosophy, epistemology and rational ethics: Springer.
go back to reference Dai, H.J., Chang, Y.C., Tzong-Han Tsai, R., & Hsu, W.L. (2010). New challenges for biological text-mining in the next decade. J. Comput. Sci. Technol., 25(1), 169–179.CrossRef Dai, H.J., Chang, Y.C., Tzong-Han Tsai, R., & Hsu, W.L. (2010). New challenges for biological text-mining in the next decade. J. Comput. Sci. Technol., 25(1), 169–179.CrossRef
go back to reference Damashek, M. (1995). Gauging similarity with n-grams: Language-independent categorization of text. Science, 267(5199), 843–849.CrossRef Damashek, M. (1995). Gauging similarity with n-grams: Language-independent categorization of text. Science, 267(5199), 843–849.CrossRef
go back to reference Danna, A. (2002). Gandy OscarH., J.: All that glitters is not gold: Digging beneath the surface of data mining. J. Bus. Ethics, 40(4), 373–386.CrossRef Danna, A. (2002). Gandy OscarH., J.: All that glitters is not gold: Digging beneath the surface of data mining. J. Bus. Ethics, 40(4), 373–386.CrossRef
go back to reference Dörre, J., Gerstl, P., & Seiffert, R. (1999). Text mining: finding nuggets in mountains of textual data. In Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, KDD ’99 (pp. 398–401). New York: ACM. doi:10.1145/312129.312299.CrossRef Dörre, J., Gerstl, P., & Seiffert, R. (1999). Text mining: finding nuggets in mountains of textual data. In Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, KDD ’99 (pp. 398–401). New York: ACM. doi:10.​1145/​312129.​312299.CrossRef
go back to reference Fairclough, I., & Fairclough, N. (2013). Political Discourse Analysis: A Method for Advanced Students: Taylor & Francis. Fairclough, I., & Fairclough, N. (2013). Political Discourse Analysis: A Method for Advanced Students: Taylor & Francis.
go back to reference Feldman, R., & Sanger, J. (2006). The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data: Cambridge University Press. Feldman, R., & Sanger, J. (2006). The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data: Cambridge University Press.
go back to reference François, D., Wertz, V., & Verleysen, M. (2007). The concentration of fractional distances. IEEE Transactions on Knowledge and Data Engineering, 19(7), 873–886.CrossRef François, D., Wertz, V., & Verleysen, M. (2007). The concentration of fractional distances. IEEE Transactions on Knowledge and Data Engineering, 19(7), 873–886.CrossRef
go back to reference Gamon, M., Basu, S., Belenko, D., Fisher, D., Hurst, M., & Konig, A. C. (2008). BLEWS: Using Blogs to Provide Context for News Articles. In ICWSM, 2008. Gamon, M., Basu, S., Belenko, D., Fisher, D., Hurst, M., & Konig, A. C. (2008). BLEWS: Using Blogs to Provide Context for News Articles. In ICWSM, 2008.
go back to reference Greenberg, J. (2010). There’s nothing anyone can do about it: Participation, apathy, and ”successful” democratic transition in postsocialist serbia. Slav. Rev., 69(1), 41–64.CrossRef Greenberg, J. (2010). There’s nothing anyone can do about it: Participation, apathy, and ”successful” democratic transition in postsocialist serbia. Slav. Rev., 69(1), 41–64.CrossRef
go back to reference Grosskreutz, H., Boley, M., & Krause-Traudes, M. (2010). Subgroup discovery for election analysis: A case study in descriptive data mining. In Discovery Science (pp. 57–71). Berlin Heidelberg: Springer.CrossRef Grosskreutz, H., Boley, M., & Krause-Traudes, M. (2010). Subgroup discovery for election analysis: A case study in descriptive data mining. In Discovery Science (pp. 57–71). Berlin Heidelberg: Springer.CrossRef
go back to reference Hamamoto, M., Kitagawa, H., Pan, J.Y., & Faloutsos, C. (2005). A comparative study of feature vector-based topic detection schemes a comparative study of feature vector-based topic detection schemes. In Web Information Retrieval and Integration, 2005. WIRI ’05. Proceedings. International Workshop on Challenges in (pp. 122–127). Hamamoto, M., Kitagawa, H., Pan, J.Y., & Faloutsos, C. (2005). A comparative study of feature vector-based topic detection schemes a comparative study of feature vector-based topic detection schemes. In Web Information Retrieval and Integration, 2005. WIRI ’05. Proceedings. International Workshop on Challenges in (pp. 122–127).
go back to reference He, X., & Zhang, J. (2006). Why Do Hubs Tend to Be Essential in Protein Networks PLoS Genet., 2(6). He, X., & Zhang, J. (2006). Why Do Hubs Tend to Be Essential in Protein Networks PLoS Genet., 2(6).
go back to reference Helbing, D., & Balietti, S. (2011). From social data mining to forecasting socio-economic crises. The European Physical Journal Special Topics, 195(1), 3–68.CrossRef Helbing, D., & Balietti, S. (2011). From social data mining to forecasting socio-economic crises. The European Physical Journal Special Topics, 195(1), 3–68.CrossRef
go back to reference Hong, T.P., Kuo, C.S., & Chi, S.C. (1999). Mining association rules from quantitative data. Intelligent Data Analysis, 3(5), 363–376.CrossRef Hong, T.P., Kuo, C.S., & Chi, S.C. (1999). Mining association rules from quantitative data. Intelligent Data Analysis, 3(5), 363–376.CrossRef
go back to reference Howard, P.N. (2005). Deep democracy, thin citizenship: The impact of digital media in political campaign strategy. The ANNALS of the American Academy of Political and Social Science, 597(1), 153–170. doi:10.1177/0002716204270139.CrossRef Howard, P.N. (2005). Deep democracy, thin citizenship: The impact of digital media in political campaign strategy. The ANNALS of the American Academy of Political and Social Science, 597(1), 153–170. doi:10.​1177/​0002716204270139​.CrossRef
go back to reference Jackman, S. (2001). Multidimensional Analysis of Roll Call Data via Bayesian Simulation: Identification, Estimation, Inference, and Model Checking. Polit. Anal., 9(3), 227–241.CrossRef Jackman, S. (2001). Multidimensional Analysis of Roll Call Data via Bayesian Simulation: Identification, Estimation, Inference, and Model Checking. Polit. Anal., 9(3), 227–241.CrossRef
go back to reference Jackson, P., & Moulinier, I. (2007). Natural Language Processing for Online Applications: Text retrieval, extraction and categorization. Second revised edition. Natural Language Processing: John Benjamins Publishing Company. Jackson, P., & Moulinier, I. (2007). Natural Language Processing for Online Applications: Text retrieval, extraction and categorization. Second revised edition. Natural Language Processing: John Benjamins Publishing Company.
go back to reference Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, adoption barriers and myths of open data and open government. Inf. Syst. Manag., 29(4), 258–268.CrossRef Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, adoption barriers and myths of open data and open government. Inf. Syst. Manag., 29(4), 258–268.CrossRef
go back to reference Keṡelj, V., Peng, F., Cercone, N., & Thomas, C. (2003). N-gram-based author profiles for authorship attribution. In Proceedings of the conference pacific association for computational linguistics, PACLING, (Vol. 3 pp. 255–264). Keṡelj, V., Peng, F., Cercone, N., & Thomas, C. (2003). N-gram-based author profiles for authorship attribution. In Proceedings of the conference pacific association for computational linguistics, PACLING, (Vol. 3 pp. 255–264).
go back to reference Klein, D., Smarr, J., Nguyen, H., & Manning, C.D. (2003). Named entity recognition with character-level models. In Proceedings of the seventh conference on Natural language learning at HLT-NAACL, CONLL ’03, Association for Computational Linguistics (pp. 18–183). USA: Stroudsburg. doi:10.3115/1119176.1119204. Klein, D., Smarr, J., Nguyen, H., & Manning, C.D. (2003). Named entity recognition with character-level models. In Proceedings of the seventh conference on Natural language learning at HLT-NAACL, CONLL ’03, Association for Computational Linguistics (pp. 18–183). USA: Stroudsburg. doi:10.​3115/​1119176.​1119204.
go back to reference Liu, B. (2007). Opinion mining. In Web Data Mining, Data-Centric Systems and Applications (pp. 411–447). Berlin Heidelberg: Springer. Liu, B. (2007). Opinion mining. In Web Data Mining, Data-Centric Systems and Applications (pp. 411–447). Berlin Heidelberg: Springer.
go back to reference Malouf, R., & Mullen, T. (2008). Taking sides: user classification for informal online political discourse. Internet Research, 18(2), 177–190.CrossRef Malouf, R., & Mullen, T. (2008). Taking sides: user classification for informal online political discourse. Internet Research, 18(2), 177–190.CrossRef
go back to reference Maragoudakis, M., Loukis, E., & Charalabidis, Y. (2011). A review of opinion mining methods for analyzing citizensâĂŹ contributions in public policy debate. In Electronic Participation (pp. 298–313). Berlin Heidelberg: Springe.CrossRef Maragoudakis, M., Loukis, E., & Charalabidis, Y. (2011). A review of opinion mining methods for analyzing citizensâĂŹ contributions in public policy debate. In Electronic Participation (pp. 298–313). Berlin Heidelberg: Springe.CrossRef
go back to reference Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient Estimation of Word Representations in Vector Space. In ICLR Workshop. Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient Estimation of Word Representations in Vector Space. In ICLR Workshop.
go back to reference Milošević, N. (2012). Stemmer for Serbian language: ArXiv e-prints. Milošević, N. (2012). Stemmer for Serbian language: ArXiv e-prints.
go back to reference Miner, G., Elder, J., Hill, T., Delen, D., & Fast, A. (2012). Practical Text Mining and Statistical Analysis for Non-Structured Text Data Applications. Academic Press: Academic Press. Miner, G., Elder, J., Hill, T., Delen, D., & Fast, A. (2012). Practical Text Mining and Statistical Analysis for Non-Structured Text Data Applications. Academic Press: Academic Press.
go back to reference Murray, G.R., Riley, C., & Scime, A. (2009). Pre-election polling: Identifying likely voters using iterative expert data mining. Public Opinion Quarterly, 73(1), 159–171. doi:10.1093/poq/nfp004.CrossRef Murray, G.R., Riley, C., & Scime, A. (2009). Pre-election polling: Identifying likely voters using iterative expert data mining. Public Opinion Quarterly, 73(1), 159–171. doi:10.​1093/​poq/​nfp004.CrossRef
go back to reference Nanopoulos, A., Radovanović, M., & Ivanović, M. (2009). How does high dimensionality affect collaborative filtering?. In Proceedings of the third ACM conference on Recommender systems, RecSys ’09 (pp. 293–296). USA: ACM. Nanopoulos, A., Radovanović, M., & Ivanović, M. (2009). How does high dimensionality affect collaborative filtering?. In Proceedings of the third ACM conference on Recommender systems, RecSys ’09 (pp. 293–296). USA: ACM.
go back to reference Piatetsky-Shapiro, G. (1991). Discovery, analysis and presentation of strong rules. In Knowledge Discovery in Databases (pp. 229–248): AAAI Press. Piatetsky-Shapiro, G. (1991). Discovery, analysis and presentation of strong rules. In Knowledge Discovery in Databases (pp. 229–248): AAAI Press.
go back to reference PÃtry, F., Collette. (2009) In L.M. Imbeau (Ed.), Measuring how political parties keep their promises: A positive perspective from political science (Vol. 15, pp. 65–80). New York : Springer. PÃtry, F., Collette. (2009) In L.M. Imbeau (Ed.), Measuring how political parties keep their promises: A positive perspective from political science (Vol. 15, pp. 65–80). New York : Springer.
go back to reference Rana, N., Dwivedi, Y., & Williams, M. (2013). A meta-analysis of existing research on citizen adoption of e-government. Inf. Syst. Front., 1–17. Rana, N., Dwivedi, Y., & Williams, M. (2013). A meta-analysis of existing research on citizen adoption of e-government. Inf. Syst. Front., 1–17.
go back to reference Ratkiewicz, J., Conover, M., Meiss, M., Gonçalves, B., Flammini, A., & Menczer, F. (2011). Detecting and tracking political abuse in social media. In Proc. 5th International AAAI Conference on Weblogs and Social Media (ICWSM). Ratkiewicz, J., Conover, M., Meiss, M., Gonçalves, B., Flammini, A., & Menczer, F. (2011). Detecting and tracking political abuse in social media. In Proc. 5th International AAAI Conference on Weblogs and Social Media (ICWSM).
go back to reference Sanches, P., Svee, E.O., Bylund, M., Hirsch, B., & Boman, M. (2013). Knowing your population: Privacy-sensitive mining of massive data Vol. 1: Network and Communication Technologies. Sanches, P., Svee, E.O., Bylund, M., Hirsch, B., & Boman, M. (2013). Knowing your population: Privacy-sensitive mining of massive data Vol. 1: Network and Communication Technologies.
go back to reference Scharl, A., & Weichselbraun, A. (2008). An automated approach to investigating the online media coverage of U.S. presidential elections. Journal of Information Technology and Politics, 5 (1), 121–132. doi:10.1080/19331680802149582.CrossRef Scharl, A., & Weichselbraun, A. (2008). An automated approach to investigating the online media coverage of U.S. presidential elections. Journal of Information Technology and Politics, 5 (1), 121–132. doi:10.​1080/​1933168080214958​2.CrossRef
go back to reference Seo, Y.W., & Sycara, K. (2004). Text clustering for topic detection. Tech. Rep. CMU-RI-TR-04-03. Pittsburgh: Robotics Institute. Seo, Y.W., & Sycara, K. (2004). Text clustering for topic detection. Tech. Rep. CMU-RI-TR-04-03. Pittsburgh: Robotics Institute.
go back to reference Stamatatos, E. (2009). Intrinsic plagiarism detection using character n-gram profiles. In 3rd PAN Workshop. Uncovering Plagiarism, Authorship and Social Software Misuse (pp. 38–46). Stamatatos, E. (2009). Intrinsic plagiarism detection using character n-gram profiles. In 3rd PAN Workshop. Uncovering Plagiarism, Authorship and Social Software Misuse (pp. 38–46).
go back to reference Stieglitz, S., & Dang-Xuan, L. (2012). Social media and political communication: a social media analytics framework. Soc. Netw. Anal. Min., 1–15. Stieglitz, S., & Dang-Xuan, L. (2012). Social media and political communication: a social media analytics framework. Soc. Netw. Anal. Min., 1–15.
go back to reference Tomašev, N., & Mladenić, D. (2012). Nearest neighbor voting in high dimensional data: Learning from past occurrences. Computer Science and Information Systems, 9, 691–712.CrossRef Tomašev, N., & Mladenić, D. (2012). Nearest neighbor voting in high dimensional data: Learning from past occurrences. Computer Science and Information Systems, 9, 691–712.CrossRef
go back to reference Tomašev, N., Radovanović, M., Mladenić, D., & Ivanović, M. (2013). The role of hubness in clustering high-dimensional data. IEEE Trans. Knowl. Data Eng., 99(PrePrints), 1. Tomašev, N., Radovanović, M., Mladenić, D., & Ivanović, M. (2013). The role of hubness in clustering high-dimensional data. IEEE Trans. Knowl. Data Eng., 99(PrePrints), 1.
go back to reference Tomašev, N., Radovanović, M., Mladenić, D., & Ivanovicć, M. (2011). A probabilistic approach to nearest neighbor classification: Naive hubness bayesian k-nearest neighbor. In Proceeding of the CIKM conference. Tomašev, N., Radovanović, M., Mladenić, D., & Ivanovicć, M. (2011). A probabilistic approach to nearest neighbor classification: Naive hubness bayesian k-nearest neighbor. In Proceeding of the CIKM conference.
go back to reference Uramoto, N., Matsuzawa, H., Nagano, T., Murakami, A., Takeuchi, H., & Takeda, K. (2004). A text-mining system for knowledge discovery from biomedical documents. IBM Syst. J., 43(3), 516–533.CrossRef Uramoto, N., Matsuzawa, H., Nagano, T., Murakami, A., Takeuchi, H., & Takeda, K. (2004). A text-mining system for knowledge discovery from biomedical documents. IBM Syst. J., 43(3), 516–533.CrossRef
go back to reference Vachudova, M.A. (2009). Corruption and compliance in the EU’s post-communist members and candidates. JCMS: Journal of Common Market Studies, 47, 43–62. Vachudova, M.A. (2009). Corruption and compliance in the EU’s post-communist members and candidates. JCMS: Journal of Common Market Studies, 47, 43–62.
go back to reference Vaidya, J. (2012). Privacy in the context of digital government. In Proceedings of the 13th Annual International Conference on Digital Government Research, dg.o ’12 (pp. 302–303). New York: ACM. doi:10.1145/2307729.2307796. Vaidya, J. (2012). Privacy in the context of digital government. In Proceedings of the 13th Annual International Conference on Digital Government Research, dg.o ’12 (pp. 302–303). New York: ACM. doi:10.​1145/​2307729.​2307796.
go back to reference Vitas, D., Krstev, C., Obradović, I., Popović, L., & Pavlović-Lazetić, G. (2003). An overview of resources and basic tools for processing of Serbian written texts. Vitas, D., Krstev, C., Obradović, I., Popović, L., & Pavlović-Lazetić, G. (2003). An overview of resources and basic tools for processing of Serbian written texts.
go back to reference Vlado, K., & Šipka, D. (2008). A suffix subsumption-based approach to building stemmers and lemmatizers for highly inflectional languages with sparse resources. INFOTHECA. Can. J. Inf. Libr. Sci., 9(1), 23–33. Vlado, K., & Šipka, D. (2008). A suffix subsumption-based approach to building stemmers and lemmatizers for highly inflectional languages with sparse resources. INFOTHECA. Can. J. Inf. Libr. Sci., 9(1), 23–33.
go back to reference Wartena, C., & Brussee, R. (2008). Topic detection by clustering keywords. In 19th International Workshop on Database and Expert Systems Application, 2008. DEXA ’08 (pp. 54– 58). Wartena, C., & Brussee, R. (2008). Topic detection by clustering keywords. In 19th International Workshop on Database and Expert Systems Application, 2008. DEXA ’08 (pp. 54– 58).
go back to reference Weber, I., Garimella, V.R.K., & Borra, E. (2012). Political search trends. In Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval, SIGIR ’12 (pp. 1012–1012). New York: ACM. doi:10.1145/2348283.2348437. Weber, I., Garimella, V.R.K., & Borra, E. (2012). Political search trends. In Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval, SIGIR ’12 (pp. 1012–1012). New York: ACM. doi:10.​1145/​2348283.​2348437.
go back to reference Weerakkody, V., Irani, Z., Lee, H., Osman, I., & Hindi, N. (2013). E-government implementation: A birdâĂŹs eye view of issues relating to costs, opportunities, benefits and risks. Inf. Syst. Front., 1–27. Weerakkody, V., Irani, Z., Lee, H., Osman, I., & Hindi, N. (2013). E-government implementation: A birdâĂŹs eye view of issues relating to costs, opportunities, benefits and risks. Inf. Syst. Front., 1–27.
go back to reference Witten, I.H., & Frank, E. (2005). Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems). USA: Morgan Kaufmann Publishers Inc. Witten, I.H., & Frank, E. (2005). Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems). USA: Morgan Kaufmann Publishers Inc.
go back to reference Zhong, N., Li, Y., & Wu, S.T. (2012). Effective pattern discovery for text mining. Knowledge and Data Engineering. IEEE Transactions on, 24(1), 30–44. Zhong, N., Li, Y., & Wu, S.T. (2012). Effective pattern discovery for text mining. Knowledge and Data Engineering. IEEE Transactions on, 24(1), 30–44.
Metadata
Title
Extracting the patterns of truthfulness from political information systems in Serbia
Author
Nenad Tomašev
Publication date
26-09-2015
Publisher
Springer US
Published in
Information Systems Frontiers / Issue 1/2017
Print ISSN: 1387-3326
Electronic ISSN: 1572-9419
DOI
https://doi.org/10.1007/s10796-015-9596-8

Other articles of this Issue 1/2017

Information Systems Frontiers 1/2017 Go to the issue

Premium Partner