Biden vs Trump: Modeling US General Elections Using BERT Language Model
Social media plays a crucial role in shaping the worldview during election campaigns. Social media has been used as a medium for political campaigns and a tool for organizing protests; some of which have been peaceful, while others have led to riots. Previous research indicates that understanding us...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9530657/ |
| _version_ | 1818576581461803008 |
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| author | Rohitash Chandra Ritij Saini |
| author_facet | Rohitash Chandra Ritij Saini |
| author_sort | Rohitash Chandra |
| collection | DOAJ |
| description | Social media plays a crucial role in shaping the worldview during election campaigns. Social media has been used as a medium for political campaigns and a tool for organizing protests; some of which have been peaceful, while others have led to riots. Previous research indicates that understanding user behaviour, particularly in terms of sentiments expressed during elections can give an indication of the election outcome. Recently, there has been tremendous progress in language modelling with deep learning via <italic>long short-term memory</italic> (LSTM) models and variants known as <italic>bidirectional encoder representations from transformers</italic> (BERT). Motivated by these innovations, we develop a framework to model the US general elections. We investigate if sentiment analysis can provide a means to predict election outcomes. We use the LSTM and BERT language models for Twitter sentiment analysis leading to the US 2020 presidential elections. Our results indicate that sentiment analysis can provide a general basis for modelling election outcomes where the BERT model indicates Biden winning the elections. |
| first_indexed | 2024-12-16T06:16:18Z |
| format | Article |
| id | doaj.art-aa32a5c1a8f24126878d8f09464797c1 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T06:16:18Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-aa32a5c1a8f24126878d8f09464797c12022-12-21T22:41:15ZengIEEEIEEE Access2169-35362021-01-01912849412850510.1109/ACCESS.2021.31110359530657Biden vs Trump: Modeling US General Elections Using BERT Language ModelRohitash Chandra0https://orcid.org/0000-0001-6353-1464Ritij Saini1School of Mathematics and Statistics, University of New South Wales, Sydney, NSW, AustraliaDepartment of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai, IndiaSocial media plays a crucial role in shaping the worldview during election campaigns. Social media has been used as a medium for political campaigns and a tool for organizing protests; some of which have been peaceful, while others have led to riots. Previous research indicates that understanding user behaviour, particularly in terms of sentiments expressed during elections can give an indication of the election outcome. Recently, there has been tremendous progress in language modelling with deep learning via <italic>long short-term memory</italic> (LSTM) models and variants known as <italic>bidirectional encoder representations from transformers</italic> (BERT). Motivated by these innovations, we develop a framework to model the US general elections. We investigate if sentiment analysis can provide a means to predict election outcomes. We use the LSTM and BERT language models for Twitter sentiment analysis leading to the US 2020 presidential elections. Our results indicate that sentiment analysis can provide a general basis for modelling election outcomes where the BERT model indicates Biden winning the elections.https://ieeexplore.ieee.org/document/9530657/Language modelsdeep learningelection modellingsentiment analysisBERTUS elections |
| spellingShingle | Rohitash Chandra Ritij Saini Biden vs Trump: Modeling US General Elections Using BERT Language Model IEEE Access Language models deep learning election modelling sentiment analysis BERT US elections |
| title | Biden vs Trump: Modeling US General Elections Using BERT Language Model |
| title_full | Biden vs Trump: Modeling US General Elections Using BERT Language Model |
| title_fullStr | Biden vs Trump: Modeling US General Elections Using BERT Language Model |
| title_full_unstemmed | Biden vs Trump: Modeling US General Elections Using BERT Language Model |
| title_short | Biden vs Trump: Modeling US General Elections Using BERT Language Model |
| title_sort | biden vs trump modeling us general elections using bert language model |
| topic | Language models deep learning election modelling sentiment analysis BERT US elections |
| url | https://ieeexplore.ieee.org/document/9530657/ |
| work_keys_str_mv | AT rohitashchandra bidenvstrumpmodelingusgeneralelectionsusingbertlanguagemodel AT ritijsaini bidenvstrumpmodelingusgeneralelectionsusingbertlanguagemodel |