Tímea Emese Tóth

Assistant lecturer

Tímea Emese Tóth

Assistant lecturer

Tímea Emese Tóth is a survey statistician. She is currently a PhD student at the Interdisciplinary Social Research Program at the Faculty of Social Sciences of ELTE, and she is also an assistant lecturer at the Methodology Department of Social Research from the academic year 2021/22. She conducted her thesis research in the framework of the research group under the supervision of Márton Rakovics. She tried to detect typical attitudes in the sustainability discourse on Twitter by sentiment analysis and topical modelling. The main research question of her dissertation tries to answer the question of what changes have taken place in sustainability communication at the levels of the Hungarian digital public sphere since the early 2000s, what trends are currently in place, and whether there is a flow of such communication between different areas. Her current supervisor is Dr. János Balázs Kocsis, Associate Professor at Corvinus University. She uses Natural Language Processing (NLP) as a methodological approach.



Title: Analysing sustainability in the triad of political publicity, online media platforms and the lay public

PhD student: Emese Tímea Tóth

Supervisor: Dr. János Balázs Kocsis


The main aim of the doctoral research is to assess, with the help of the method of computer text analytics, what changes have taken place in sustainability communication at the levels of the Hungarian digital spheres since the early 2000s, what trends are still in place, and whether there is a flow of information between the professional, lay, political and the journalistic spheres involved in the sustainability discourse, which can be clearly distinguished.

The turbulent period from 2001 to 2020 is not only significant in terms of events (entry into force of the Kyoto Protocol [2005], the National Climate Change Strategy [Act LX of 2007], the entry into force of the Paris Agreement [2006]), but also in terms of the importance of the online public sphere. The latter phenomenon gives us the opportunity to explore and understand the characteristics of spheres through automated processing of the constantly evolving text stream to a degree that was not previously possible (Rockstörm, Klum 2015; Raworth, 2017; Goulson, 2019; Dasgupta, McKenzie, 2020; IPCC, 2020; Németh, Katona, Kmetty, 2020; Németh, Koltai, 2021).

Examining the dynamics of online publicity through temporal comparisons can be done using dynamic and structural topical models and relevant NLP methods (e.g. sentiment analysis), resulting in more nuanced textual interpretability. The identification, implementation and validation of methods for analysing the transnational nature of online public sphere is also within the scope of this dissertation, together with the comparison of results with traditional survey methods (Tikk, 2007; Turney, Pantel, 2010; Blei et al, 2003; Mikolov et al, 2013; Alessia et al, 2015; Hutto, Gilbert, 2015; Sankar-Subramaniyaswamy, 2017)




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Hutto, C.J., Gilbert, Eric. (2015). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. Proceedings of the 8th International Conference on Weblogs and Social Media, ICWSM 2014.

Intergovernmental Panel on Climate Change – The IPCC and the Sixth Assessment Cycle, (2020).  https://www.ipcc.ch/site/assets/uploads/2020/05/2020-AC6_en.pdf [letöltve: 2021.03.06.]

Mikolov, T., Chen, K., Corrado, G. & Dean, J. (2013). Efficient estimation of word representations in vector space. arXiv preprint, arXiv:1301.3781.

Németh, R., Katona, E. R., Kmetty, Z. (2020) Az automatizált szövegelemzés perspektívája a társadalomtudományokban. SZOCIOLÓGIAI SZEMLE, 30 (1). pp. 44-62. ISSN 1216-2051

Németh, R., Koltai, J. (2021) The Potential of Automated Text Analytics in Social Knowledge Building. In: Rudas T., Péli G. (eds) Pathways Between Social Science and Computational Social Science. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-54936-7_3

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Sankar, H., Subramaniyaswamy, V. (2017). “Investigating sentiment analysis using machine learning approach,” 2017 International Conference on Intelligent Sustainable Systems (ICISS), Palladam, India, 2017, pp. 87-92, doi: 10.1109/ISS1.2017.8389293.

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Turney, P. D., Pantel, P. (2010). From frequency to meaning: Vector Space Models of semantics. journal of Artificial Intelligence Research, 37, 141–188.

Turney, P. D., Pantel, P. (2010). From frequency to meaning: Vector Space Models of semantics. journal of Artificial Intelligence Research, 37, 141–188.




Title: How has the COVID-19 pandemic redefined the concept of sustainability in the lay public? Narratives and communication strategies.

PhD student: Emese Tímea Tóth

Supervisor: Dr. János Balázs Kocsis


The UNKP research aims to analyse lay public narratives that explicitly link the COVID-19 pandemic to the issue of sustainability.

The two phenomena (pandemic and sustainability) can be linked at several points. First of all, the pandemic situation, according to many authors, is self-inflicted by humanity through the pursuit of activities where infectious microorganisms are able to spread from animal to human. (IBPES 2020; SETTELE ET AL. 2020)

In addition, several studies highlight that the epidemic has stimulated people to adopt mindsets and operational mechanisms that are aligned with the goals of sustainable development and that focus attention on, for example, climate change and increased awareness of its signs. (GALVANI, LEW, PEREZ, 2020; HORTAY, STEFKOVICS, 2021) The key to avoiding similar situations in the future would be, among others (BIGLIERI, VIDOVICH, KEIL, 2020; CONNOLL, ALI, KEIL, 2020; ACUTO ET AL, 2020; DASGUPTA, MCKENZIE, 2020; SOLOW, 1974, STEFFEN ET AL., 2015; DREWS, ANTAL, 2016; DREWS, REESE, 2018), if, first and foremost, a transformation towards sustainability is achieved in social, economic, technological and spatial terms, while at the same time challenging paradigms that make infinite unsustainable growth and profit-making the primary goal.

Finally, Raworth argues that a focus on health, an adequate income-labour ratio, peace and justice, social and gender equality and education are all aspects that should be given priority (RAWORTH, 2017), and ideally converge in the hands of political leaders, making sustainability a relevant public policy issue. Without knowledge of society, without knowledge of the opinions and positions of the individuals who make it up, no legitimate professional and political decisions can be made, says the primary guide to sustainability, David Attenborough. This is confirmed by the authors Bodenheimer and Leidenberger, who add that coordinated action based on appropriate policy choices is best achieved through conscious planning and carefully designed strategic communication to the public. (ATTENBOROUGH, HUGHES, 2020; BODENHEIMER, LEIDENBERGER, 2020)

The aim of our research is to examine the public representation of these discourses. After creating a corpus in Hungarian defined by a keyword search, we analyse texts generated by the lay public on social media platforms, blogs, online newspapers, comment sections of magazines. We focus on digital public manifestations that deal with both phenomena (pandemics and sustainability). The analysis is performed using topical modelling, which assumes that there are words with strong semantic information and that documents dealing with a similar topic use similar groups of words. (BLEI ET AL, 2003) The method can also be used to understand the society represented in the online space and the set of narratives they represent, which can provide a basis for designing the strategic communication to the public mentioned earlier.



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