Measuring the Similarities of Twitter Hashtags for Agriculture in the Czech Language
DOI:
https://doi.org/10.7160/aol.2019.110410How to Cite
Abstract
Our paper presents first analysis of Czech Twitter content within the agriculture context. We deployed textual analysis of more than 240,000 tweets over 2014-2019 hashtags that were, according to Google Trends, most trending and related to Czech agriculture such as #dotace, #repka, or #bionafta – both in Czech and English language. Besides descriptive statistics of the tweet dataset, we visualized keyword correlations which revealed strong focus of the discourse on rapeseed, biofuel and the prime minister Andrej Babiš. Owing to inherent political context of the given hashtags, we found spikes in topics which followed the public attention to the topics in mass media. We also found several accounts that produces high traffic for certain hashtags in Czech, yet those accounts were located abroad. Consistent with other studies, a high proportion of tweets was generated by unverified accounts that might be bots – automated accounts. We propose to conduct semantic analysis of a broader dataset over the main social media platforms in the Czech Republic.References
Bordag, S. (2008) “A comparison of co-occurrence and similarity measures as simulations of context”, International Conference on Intelligent Text Processing and Computational Linguistics. pp 52-63. ISSN 0302-9743. DOI: https://doi.org/10.1007/978-3-540-78135-6_5
Campoy, A. (2019) “More than 60% of Donald Trump’s Twitter followers look suspiciously fake”. [Online]. Available: https://qz.com/1422395/how-many-of-donald-trumps-twitter-followers-are-fake/ [Accessed: 28 Nov. 2019].
Carré, P. and Pouzet, A. (2014) “Rapeseed market, worldwide and in Europe”, Oilseeds and fats, Crops and Lipids, Vol. 21, No. 1. E-ISSN 2257-6614, ISSN 2272-6977. DOI: https://doi.org/10.1051/ocl/2013054
Červenková, E., Šimek, P., Vogeltanzová, T. and Stočes, M., (2011) “Social networks as an integration tool in rural areas–agricultural enterprises of the Czech Republic”, AGRIS on-line Papers in Economics and Informatics, Vol. 3, No. 1, pp 53-60. ISSN 1804–1930.
Church, K. W. and Hanks, P. (1990) „Word association norms, mutual information, and lexicography“, Proceeding of ACL ‚89 Proceedings of the 27th annual meeting on Association for Computational Linguistics, pp. 76-83. DOI: https://doi.org/10.3115/981623.981633
Dickerson, J. P., Kagan, V. and Subrahmanian, V. S. (2014) “Using sentiment to detect bots on twitter: Are humans more opinionated than bots?”, In Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, pp 620-627. IEEE Press. E-ISBN 978-1-4799-5877-1. DOI: https://doi.org/10.1109/ASONAM.2014.6921650
Jansen, B. J., Zhang, M., Sobel, K. and Chowdury, A. (2009) “Twitter power: Tweets as electronic word of mouth”, Journal of the American society for information science and technology, Vol. 60, No. 11, pp 2169-2188. E-ISSN 2330-1643. DOI: https://doi.org/10.1002/asi.21149
Kołodziejczak, A. and Kossowski, T. (2011) “Diversification of farming systems in Poland in the years 2006-2009”, Quaestiones Geographicae, Vol. 30, No. 2, pp 49-56. ISSN 0137-477X. DOI: https://doi.org/10.2478/v10117-011-0017-x
Lund, K. and Burgess, C. (1996) “Producing high-dimensional semantic spaces from lexical co-occurrence”, Behavior research methods, instruments, & computers, Vol. 28, No. 2, pp 203-208. E-ISSN 1554-3528. DOI: https://doi.org/10.3758/BF03204766
Mazurek, G., Korzyński, P. and Górska, A. (2019) „Social Media in the Marketing of Higher Education Institutions in Poland: Preliminary Empirical Studies“, Entrepreneurial Business and Economics Review, Vol. 7, No. 1, pp 117-133. E-ISSN 2353-8821, ISSN 2353-883X. DOI: https://doi.org/10.15678/EBER.2019.070107
Miller, G. A. and Charles, W. G. (1991) “Contextual correlates of semantic similarity”, Language and cognitive processes, Vol. 6, No. 1, pp 1-28. E-ISSN 2327-3801, ISSN 2327-3798. DOI: https://doi.org/10.1080/01690969108406936
Orhan, M.A. (2017) „ The Evolution of the Virtuality Phenomenon in Organizations: A Critical Literature Review“, Entrepreneurial Business and Economics Review, Vol. 5, No. 4, pp. 171-188. E-ISSN 2353-8821, ISSN 2353-883X. DOI: https://doi.org/10.15678/EBER.2017.050408
Ozdikis, O., Senkul, P. and Oguztuzun, H. (2012) “Semantic expansion of hashtags for enhanced event detection in Twitter”, Conference: VLDB Workshop on Online Social Systems (WOSS 2012), Istanbul. DOI: https://doi.org/10.1109/ASONAM.2012.14
Pehe, J. (2018) “Czech Democracy Under Pressure”, Journal of Democracy, Vol. 29, No. 3, pp. 65-77. E-ISSN 1045-5736, ISSN 1086-3214. DOI: https://doi.org/10.1353/jod.2018.0045
Reiff M., Surmanová K., Balcerzak A. P. and Pietrzak M. B. (2016) „Multiple Criteria Analysis of European Union Agriculture“, Journal of International Studies, Vol. 9, No 3, pp. 62-74. E-ISSN 2071-8330, ISSN 2306-3483. DOI: https://doi.org/10.14254/2071-8330.2016/9-3/5
Spence, D. P. and Owens, K. C. (1990) “Lexical co-occurrence and association strength”, Journal of Psycholinguistic Research, Vol. 19, No. 5, pp. 317-330. E-ISSN 1573-6555, ISSN 0090-6905. DOI: https://doi.org/10.1007/BF01074363
Svatoš, M. and Smutka, L. (2009) “Influence of the EU enlargement on the agrarian foreign trade development in member states”, Agricultural Economics (AGRICECON), Vol. 55, No. 5, pp. 233-249. ISSN 0139-570X. DOI: https://doi.org/10.17221/34/2009-AGRICECON
Turney, P. D. (2001) “Mining the web for synonyms: PMI-IR versus LSA on TOEFL”, Proceedings of the 12ve European Conference on Machine Learning, pp. 491-502. Springer, Berlin, Heidelberg. DOI: https://doi.org/10.1007/3-540-44795-4_42
Vaněk, J., Šimek, P., Vogeltanzová, T., Červenková, E. and Jarolímek, J. (2010) “ICT in Agricultural Enterprises in the Czech Republic–Exploration 2010”, Agris on-line Papers in Economics and Informatics, Vol. 2, No. 3, pp 69-75. ISSN 1804–1930
Wald, R. and Khoshgoftaar, T. M., Napolitano, A. and Sumner, C. (2013) “Predicting susceptibility to social bots on twitter”, 14th International Conference on Information Reuse & Integration (IRI), IEEE Computer Society, pp. 6-13.
Wątróbski, J., Jankowski, J. and Ziemba, P. (2016) „Multistage Performance Modelling in Digital Marketing Management“, Economics and Sociology, Vol. 9, No. 2, pp. 101-125. ISSN 2071-789X. DOI: https://doi.org/10.14254/2071-789X.2016/9-2/7
Xu, Z., Ru, L., Xiang, L. and Yang, Q. (2011) “Discovering user interest on twitter with a modified author-topic model”, Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, , Vol. 1, pp. 422-429. DOI: https://doi.org/10.1109/WI-IAT.2011.47








