USA INAUGURAL SPEECH: A STATISTICAL APPROACH

Dimitri Calipolitis; Carla Pleștiu

doi:10.12955/pss.v4.393

Authors

Dimitri Calipolitis Bucharest University of Economic Studies, Faculty of Economic Cybernetics, Statistics and Informatics, Department of Statistics and Econometrics
Carla Pleștiu Bucharest University of Economic Studies, Faculty of Economic Cybernetics, Statistics and Informatics, Department of Statistics and Econometrics

DOI:

https://doi.org/10.12955/pss.v4.393

Abstract

The aim of this study is to determine the statistical characteristics of the terms present in the inaugural speeches of the elected American presidents, from the year 2000 to date. The methods applied belong to text mining and they determined the existence of a specific distribution of terms (Zipf and Heaps law), the correlation between certain words, the frequency of terms (alongside TF–IDF), the lexical variation within the speeches (Type–Token Ration, Hapax Richness), as well as the type of sentiment extracted by comparing specific sentiment lexicons (Afinn versus Bing). Thus, from a quantitative point of view and based on the results obtained in R, it is possible to deduce which terms will be used in the following inaugural speeches of future American presidents. This paper was co-financed by the Bucharest University of Economic Studies as part of the PhD programme.

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References

Bulgakova, Y., Shabanova, V., & Eliseeva, A. (2018). The Language of Leadership: Analyzing Public Speeches of Presidents (Literature Review). Springer Proceedings in Business and Economics, 69–77.

Cramer, H. (1946). Mathematical Methods of Statistics. Princeton: Princeton University Press.

Dilai, M. , Onukevych, Y., & Dilay I. Sentiment Analysis of the US and Ukrainian Presidential Speeches. Proceedings of the 2nd International Conference Computational Linguistics And Intelligent Systems, Vol. 2, 60-70.

Feldman, R., & Sanger, J. (2007). The text mining handbook: Advanced approaches in analyzing unstructured data. Cambridge University Press.

Heaps, Harold Stanley (1978), Information Retrieval: Computational and Theoretical Aspects, Academic Press.

Hu, Minqing, and Bing Liu. (2004). Mining and summarizing customer reviews. KDD-2004 - Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 168–77. https://doi.org/10.1145/1014052.1014073.

Jockers, Matthew L., and Rosamond Thalken. (2020). Text Analysis with R: For Students of Literature. 2nd ed. Cham, Switzerland: Springer Nature Switzerland.

Jurafsky, D., & Martin, J. H. (2008). Speech and language processing: An introduction to natural language processing, computational linguistics, and speech recognition. Pearson Prentice Hall.

Kumar, Ashish, and Avinash Paul. (2016). Mastering Text Mining with R. Birmingham, United Kingdom: Packt Publishing.

Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to information retrieval. Cambridge University Press.

Matthews, B. W. (1975). Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochimica et Biophysica Acta (BBA) - Protein Structure. 405 (2): 442–451. doi:10.1016/0005-2795(75)90109-9.

Niekler, A. and G. Wiedemann. (2020). Text mining in R for the social sciences and digital humanities. Retrievable from https://tm4ss.github.io/docs/index.html

Nielsen, Finn Årup. (2011). A new ANEW: Evaluation of a word list for sentiment analysis in microblogs. In CEUR Workshop Proceedings, 718:93–98. http://arxiv.org/abs/1103.2903.

Rajaraman, A., & Ullman, J. D. (2011). Data Mining. Mining of Massive Datasets, 1–17. doi:10.1017/cbo9781139058452.002

Saeed, R. (2014). A Speech Act Analysis of American Presidential Speeches. Arts Journal, 110, 1-40.

Silge, J and D. Robinson. (2017). Text Mining with R: A Tidy Approach. Sebastopol, California: O'Reilly Media.

Thomas, D. (2005a). Type-token Ratios in One Teacher's Classroom Talk: An Investigation of Lexical Complexity.

Zhang, Z. (2018). Text Mining for Social and Behavioral Research Using R: A Case Study on Teaching Evaluation. Retrievable from https://books.psychstat.org/textmining.

Zipf, George K. (1949). Human Behavior and the Principle of Least Effort. Cambridge, Massachusetts: Addison-Wesley.

USA INAUGURAL SPEECH: A STATISTICAL APPROACH

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