Abstract
In this chapter we present computational social science methods to identify latent informal networks of the political elite in a specific era of Hungarian history. After World War 2, a politically intense period began in Hungary under the leadership of the Hungarian Workers’ Party (HWP) with its characteristic and highly influential main secretary, Mátyás Rákosi. This era (widely known as Rákosi era) was tainted by the terror and paranoia produced by the constant struggle for power. In such a political climate, most political positions depended on an informal network among politicians.
Computational science methods make it possible to analyze our historical sources in novel ways by handling big volumes of information. We use two written historical sources to model how joint political participation can manifest in informal connections between politicians. In this study our main approach is natural language processing, ontological analysis, and social network analysis. We model the latent informal networks of party members referred to in the sources by creating their communication networks. These are then used to analyze the elite positions of various party members in key network positions.
Our results suggest that some party members in certain positions in communication networks may be closely related to the elite despite their inferior political positions. Thus, we conclude that just discussing the elite in the traditional “positional elite” terms is questionable. By introducing the notion of the “discursive elite,” we take a step further in the elite research methodology of the studied era.
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Notes
- 1.
In recent decades the volume of digitized text (originally paper-based sources) that permitted corpora-building in Hungarian has grown dramatically (Simon and Sass 2012:1–2). However, to the best of our knowledge, there is only one large and freely available Hungarian historical corpus, the so-called Magyar Történeti Szövegtár (MTSZ, Hungarian Historical Text Collection), containing also texts produced during the era in question. Though this corpus has a number of advantages (for instance, it consists of a vast volume of documents, representing hundreds of years of language usage), it also has some notable disadvantages concerning the query opportunities of the corpus. In addition, querying of the semantic features of the database is not possible.
- 2.
The numerical suffix of these actors corresponds to their identifier in the personnel database used for their identification.
- 3.
István Friss (1903–1978) was the executive of the State Economics Department then later the Planning, Finance, and Trade Department.
- 4.
For this study the Protege tool is used. It is a free, open-source ontology editor that serves as a framework for building intelligent systems. This program was chosen after considering easy accessibility and operability and because it fully supports the latest c(OWL 2).
- 5.
During the encoding process, the code table was enriched by the words of a given agenda item that is assigned a given topic in the ontology. Of course as more items are included, the association list (word codes) increases significantly and results in overfitting.
- 6.
A similar method was applied by Leo S. Gregory during the network analysis of the Political Committee of the Chinese Communist Party. There political topics were defined not through CAP codes but the public political statements (Gregory 2013).
- 7.
Free People (“Szabad Nép”) was the daily newspaper of the communist parties (first the MKP then the HWP) between 1942 and 1956.
- 8.
Troika corresponds to the three key politicians of this era: Mátyás Rákosi, Ernő Gerő, and Mihály Farkas. “Trojka” is best translated as “trio.”
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Gulyás, A., Szabó, M.K., Ring, O., Kiss, L., Boros, I. (2021). Networks of the Political Elite and Political Agenda Topics: Creation and Analysis of Historical Corpora Using NLP and SNA Methods. 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_9
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