Prediction of Political Leanings of Chinese Speaking Twitter Users
This work presents a supervised method for generating a classifier model of the stances held by Chinese-speaking politicians and other Twitter users. Many previous works of political tweets prediction exist on English tweets, but to the best of our knowledge, this is the first work that builds predi...
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| Main Authors | , |
|---|---|
| Format | Journal Article |
| Language | English |
| Published |
11.10.2021
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| Online Access | Get full text |
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| Abstract | This work presents a supervised method for generating a classifier model of
the stances held by Chinese-speaking politicians and other Twitter users. Many
previous works of political tweets prediction exist on English tweets, but to
the best of our knowledge, this is the first work that builds prediction model
on Chinese political tweets. It firstly collects data by scraping tweets of
famous political figure and their related users. It secondly defines the
political spectrum in two groups: the group that shows approvals to the Chinese
Communist Party and the group that does not. Since there are not space between
words in Chinese to identify the independent words, it then completes
segmentation and vectorization by Jieba, a Chinese segmentation tool. Finally,
it trains the data collected from political tweets and produce a classification
model with high accuracy for understanding users' political stances from their
tweets on Twitter. |
|---|---|
| AbstractList | This work presents a supervised method for generating a classifier model of
the stances held by Chinese-speaking politicians and other Twitter users. Many
previous works of political tweets prediction exist on English tweets, but to
the best of our knowledge, this is the first work that builds prediction model
on Chinese political tweets. It firstly collects data by scraping tweets of
famous political figure and their related users. It secondly defines the
political spectrum in two groups: the group that shows approvals to the Chinese
Communist Party and the group that does not. Since there are not space between
words in Chinese to identify the independent words, it then completes
segmentation and vectorization by Jieba, a Chinese segmentation tool. Finally,
it trains the data collected from political tweets and produce a classification
model with high accuracy for understanding users' political stances from their
tweets on Twitter. |
| Author | Jiang, Duoji Gu, Fenglei |
| Author_xml | – sequence: 1 givenname: Fenglei surname: Gu fullname: Gu, Fenglei – sequence: 2 givenname: Duoji surname: Jiang fullname: Jiang, Duoji |
| BackLink | https://doi.org/10.48550/arXiv.2110.05723$$DView paper in arXiv |
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| Snippet | This work presents a supervised method for generating a classifier model of
the stances held by Chinese-speaking politicians and other Twitter users. Many... |
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| SubjectTerms | Computer Science - Artificial Intelligence Computer Science - Computation and Language Computer Science - Computers and Society |
| Title | Prediction of Political Leanings of Chinese Speaking Twitter Users |
| URI | https://arxiv.org/abs/2110.05723 |
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