Proceedings of the 6th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies 2019
DOI: 10.1145/3365109.3368787
|View full text |Cite
|
Sign up to set email alerts
|

Topic Variation Detection Method for Detecting Political Business Cycles

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2021
2021
2021
2021

Publication Types

Select...
1

Relationship

1
0

Authors

Journals

citations
Cited by 1 publication
(2 citation statements)
references
References 25 publications
0
2
0
Order By: Relevance
“…Figure 13 shows the share and change point scores of the economic policy topic before and after the Lower House election that was held on February 18,1990. As shown in Fig.…”
Section: Change Point Scorementioning
confidence: 99%
See 1 more Smart Citation
“…Figure 13 shows the share and change point scores of the economic policy topic before and after the Lower House election that was held on February 18,1990. As shown in Fig.…”
Section: Change Point Scorementioning
confidence: 99%
“…This study aims to contribute in a similar scope. By extending our earlier paper (Kato et al [18]), we herein propose a new topic variation detection method and apply it to analyze a valuable, albeit underutilized, text dataset containing the Japanese Prime Minister's (PM's) detailed daily schedule for over 32 years. We aim to enhance our understanding of the empirical analysis of the political business cycle (PBC), which is a classic issue that economists and political scientists have been addressing for over four decades (Dubois [5]).…”
Section: Introductionmentioning
confidence: 99%