YouTube Comments and Party Manifestos (Japanese language)
The experiments utilized these datasets to build a system to support the design of voting advice applications. 1. Party manifesto data contains party manifestos uploaded before the 2021 Japanese Upper House and the 2022 House of Councillors elections from all the Japanese political parties. 2. YouTube comments data contains comments from the 18 most popular Japanese YouTube channels related to politics and economics uploaded between January 2021 and July 2021 (3,998,590 comments from 17,773 videos). The research was conducted by Daniil Buryakov, Mate Kovacs, Victor Kryssanov, and Uwe Serdült. Abstract of the paper: The relevance and importance of voting advice applications are demonstrated by its popularity among potential voters. On average, around 30% of voters take into account the recommendations of the applications during elections. The comparison between potential voters' and parties' positions is made on the basis of VAA policy statements on which they are asked to express opinions. VAA designers devote substantial time and effort to analyzing domestic and international politics to formulate policy statements and select those to be included in the application. In this procedure, they manually read and evaluate a large volume of publicly available data, mostly party manifestos. A problematic part of this work is the limited time frame available. This study proposes a system to assist VAA designers in formulating, revising, and selecting policy statements. Using language models and machine learning methods to process politics-related textual data, the system produces a set of suggestions corresponding to relevant VAA statements. Experiments are conducted using party manifestos and YouTube comments from Japan, combined with VAA policy statements from 6 Japanese and 2 European VAAs. The technical approaches used in the system are based on the BERT language model, which is known for its capability to capture the context of words in the documents. Although the output of the system, while not completely eliminating the need for manual human assessment, it provides valuable recommendations for updating VAA policy statements on an objective, i.e., bias-free basis.