“Popular tribunes” and their agendas: topic modelling Slovak presidents’ speeches 1993–2020

Ovádek, Michal

doi:10.1080/21599165.2020.1756785

Cited by 8 publications

(4 citation statements)

References 27 publications

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“…Another way to map the structure of international management research is to reveal which topics tend to be combined together in research articles. This is akin to examining “how (dis)similar the topics are” (Ovadek 2021 , p. 227), which can be done using clustering techniques. Figure 10 shows the dendogram obtained by conducting a hierarchical clustering on the international management topics using the Euclidian distance within Ward’s minimum variance method.…”

Section: Resultsmentioning

confidence: 99%

“…Following the recommendations of Denny and Spirling ( 2018 ), the obtained documents were subject to pre-processing and/or cleaning following the standard procedures associated with bag-of-words (Ovadek 2021 ). The obtained texts were also rearranged to make the analysis more statistically tractable.…”

Section: Methodsmentioning

confidence: 99%

“…Results showed that topic modeling can be used as a useful tool in understanding the public debate regarding the use of force as a foreign policy instrument. Recently, Ovadek ( 2021 ) used topic modeling to classify the content of 628 presidential speeches in Slovakia from 1993 to 2020. The author tracked topical variation over time for different presidents and was able to detect salient issues such as intra-executive conflict and agenda shifts.…”

Section: Related Workmentioning

confidence: 99%

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A one-hundred-year structural topic modeling analysis of the knowledge structure of international management research

Mostafa

2022

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International Management is a vast and multidisciplinary research domain that is heavily influenced by several other disciplines, such as Economics, Organizational Theory and Strategic Management. Based on 28,973 research articles, this study aims to analyze the knowledge structure of the international management domain from 1920 to 2019. Using computational text-based topic modeling analysis, we trace the evolution of international management knowledge by examining the major academic topics/latent themes discussed in the field. The study also diachronically visualizes the variations in topic prevalence over time. Our methodology is akin to “inductive mapping” as it is neither biased by our position nor it is guided by assumptions related to the topics we expect to find. Results indicate the existence of a wide variety of important research foci in the domain of international management. These include, among others, strategic alliances formation, international entry modes, corporate social responsibility, cross-cultural consumer behavior, technological innovation and entrepreneurship. Results also show that some topics such as “financial risk and return on investment” and “corporate social responsibility” show a declining time trend, indicating that academic research focusing on such topics was more likely to be published early on and less so recently. On the other hand, other topics such as “Emerging (East) Asian nations” and “global mergers and acquisitions” show an increasing trend, indicating that more papers were published recently. Taken together, although our findings might reflect the breadth and depth of research in international management, they might also suggest that the bounds of this field are not well defined.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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A one-hundred-year structural topic modeling analysis of the knowledge structure of international management research

Mostafa

2022

Qual Quant

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“…Text analysis technology can handle large amounts of information for identifying topics and opinion analysis. Some models have been used to perform this type of task, and these include latent Dirichlet allocation (LDA), support vector machines (SVMs), fuzzy domain ontology, semantic association analysis (Bohr, 2020; Claster et al , 2010; Ovádek, 2020; Tian et al , 2020).…”

Section: Introductionmentioning

confidence: 99%

Analyzing tourist data on Twitter: a case study in the province of Granada at Spain

Viñán-Ludeña

Campos

2021

JHTI

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PurposeThe main aim of this paper is to build an approach to analyze the tourist content posted on social media. The approach incorporates information extraction, cleaning, data processing, descriptive and content analysis and can be used on different social media platforms such as Instagram, Facebook, etc. This work proposes an approach to social media analytics in traveler-generated content (TGC), and the authors use Twitter to apply this study and examine data about the city and the province of Granada.Design/methodology/approachIn order to identify what people are talking and posting on social media about places, events, restaurants, hotels, etc. the authors propose the following approach for data collection, cleaning and data analysis. The authors first identify the main keywords for the place of study. A descriptive analysis is subsequently performed, and this includes post metrics with geo-tagged analysis and user metrics, retweets and likes, comments, videos, photos and followers. The text is then cleaned. Finally, content analysis is conducted, and this includes word frequency calculation, sentiment and emotion detection and word clouds. Topic modeling was also performed with latent Dirichlet association (LDA).FindingsThe authors used the framework to collect 262,859 tweets about Granada. The most important hashtags are #Alhambra and #SierraNevada, and the most prolific user is @AlhambraCultura. The approach uses a seasonal context, and the posted tweets are divided into two periods (spring–summer and autumn–winter). Word frequency was calculated and again Granada, Alhambra are the most frequent words in both periods in English and Spanish. The topic models show the subjects that are mentioned in both languages, and although there are certain small differences in terms of language and season, the Alhambra, Sierra Nevada and gastronomy stand out as the most important topics.Research limitations/implicationsExtremely difficult to identify sarcasm, posts may be ambiguous, users may use both Spanish and English words in their tweets and tweets may contain spelling mistakes, colloquialisms or even abbreviations. Multilingualism represents also an important limitation since it is not clear how tweets written in different languages should be processed. The size of the data set is also an important factor since the greater the amount of data, the better the results. One of the largest limitations is the small number of geo-tagged tweets as geo-tagging would provide information about the place where the tweet was posted and opinions of it.Originality/valueThis study proposes an interesting way to analyze social media data, bridging tourism and social media literature in the data analysis context and contributes to discover patterns and features of the tourism destination through social media. The approach used provides the prospective traveler with an overview of the most popular places and the major posters for a particular tourist destination. From a business perspective, it informs managers of the most influential users, and the information obtained can be extremely useful for managing their tourism products in that region.

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When Presidents Go Public: An Analysis of Presidential Major Speeches

Grimaldi

2023

The Informal Powers of Western European Presidents

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“Popular tribunes” and their agendas: topic modelling Slovak presidents’ speeches 1993–2020

Cited by 8 publications

References 27 publications

A one-hundred-year structural topic modeling analysis of the knowledge structure of international management research

A one-hundred-year structural topic modeling analysis of the knowledge structure of international management research

Analyzing tourist data on Twitter: a case study in the province of Granada at Spain

When Presidents Go Public: An Analysis of Presidential Major Speeches

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