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(Un)Trendy Japan: Twitter bots and the 2017 Japanese general election
Názov (Un)Trendy Japan: Twitter bots and the 2017 Japanese general election Aut.údaje Jozef Michal Mintal, Róbert Vancel Autor Mintal Jozef Michal 1992- (50%) UMBPO08 - Katedra bezpečnostných štúdií
Spoluautori Vancel Róbert 1992- (50%) UMBPO03 - Katedra medzinárodných vzťahov a diplomacie
Zdroj.dok. Politics in Central Europe : the journal of the Central European Political Science Association. Vol. 15, no. 3 (2019), pp. 497-514. - Prague : Metropolitan University Prague Press, 2019 Kľúč.slová parlamentné voľby - parliamentary elections prognózovanie - prognózy - forecasting 2017 twitter Heslá geogr. Japonsko Form.deskr. články - journal articles Jazyk dok. angličtina Krajina Česká republika Anotácia Social networking services (SNSs) can significantly impact public life during important political events. Thus, it comes as no surprise that different political actors try to exploit these online platforms for their benefit. Bots constitute a popular tool on SNSs that appears to be able to shape public opinion and disrupt political processes. However, the role of bots during political events in a non-Western context remains largely under-studied. This article addresses the question of the involvement of Twitter bots during electoral campaigns in Japan. In our study, we collected Twitter data over a fourteen-day period in October 2017 using a set of hashtags related to the 2017 Japanese general election. Our dataset includes 905,215 tweets, 665,400 of which were unique tweets. Using a supervised machine learning approach, we first built a custom ensemble classification model for bot detection based on user profile features, with an area under curve (AUC) for the test set of 0.998. Second, in applying our model, we estimate that the impact of Twitter bots in Japan was minor overall. In comparison with similar studies conducted during elections in the US and the UK, the deployment of Twitter bots involved in the 2017 Japanese general election seems to be significantly lower. Finally, given our results on the level of bots on Twitter during the 2017 Japanese general election, we provide various possible explanations for their underuse within a broader socio-political context URL Link na plný text Kategória publikačnej činnosti ADM Číslo archívnej kópie 47564 Kategória ohlasu KUMAR, Sanjay - BANSAL, Ryan - MEHTA, Raghav. A study of blending ensembles for detecting bots on twitter. In Lecture notes on data engineering and communications technologies. ISSN 2367-4512, 2021, vol. 59, pp. 29-40.
KATARYA, Rahul - MEHTA, Raghav - BANSAL, Ryan - RAINA, Pradyot - MAHALIYAN, Mukul. Bot detection in social networks using stacked generalization ensemble. In Lecture notes in electrical engineering. ISSN 1876-1100, 2021, no. 701, pp. 253-263.
TENG, Miao. Using the ship-gram model for Japanese keyword extraction based on news reports. In Complexity. ISSN 1076-2787, 2021, vol. 2021, art. no. 9965843.
RIQUELME, Fabian - RIVERA, Diego - SERRANO, Benjamin. Analyzing the far-right political action on Twitter : the Chilean constituent process. In Social network analysis and mining. ISSN 1869-5450, 2022, vol. 12, no. 1, pp. 1-19.
Katal.org. BB301 - Univerzitná knižnica Univerzity Mateja Bela v Banskej Bystrici Báza dát xpca - PUBLIKAČNÁ ČINNOSŤ Odkazy PERIODIKÁ-Súborný záznam periodika 
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