Which Emotions of Social Media Users Lead to Dissemination of Fake News: Sentiment Analysis Towards Covid-19 Vaccine

Maide Feyza Er; Yonca Bayrakdar Yılmaz

Makale detayları

Which Emotions of Social Media Users Lead to Dissemination of Fake News: Sentiment Analysis Towards Covid-19 Vaccine

Yazarlar:

Maide Feyza Er | Yonca Bayrakdar Yılmaz

Yayıncı:

Çanakkale Onsekiz Mart University

Ana Başlıklar:

Artificial Intelligence

Dergi:

Journal of Advanced Research in Natural and Applied Sciences Vol.9 Issue 1, pp.107-126

Belge Tipi:

Makale

Yayın Tarihi:

6/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001284617

pISSN:

2757-5195

Anahtar kelimeler:

Özet:

 The use of social media as a news source is quite common today. However, the fact that the news encountered on social media are accepted as true without questioning or checking their validity is one of the main reasons for the dissemination of fake news. For the social media ecosystem, the question arises as to which emotion is more effective in spreading fake news, as the accuracy and validity of the news are under the control of opinions and emotions rather than evidence-based data. From this point of view, our study investigates whether there is a relationship between users reaction to the news and the prevalence of the news. In our study, sentiment analysis was conducted on the reactions of Twitter users to fake news about the COVID-19 vaccine between December 31, 2019 and July 30, 2022. To fully assess whether there is a relationship between the reactions and the prevalence of the news, the spread of real news published in the same period in addition to fake news is also taken into consideration. Fake and real news comments, which were selected in different degrees of prevalence from the most to the least, were examined comparatively. In the study, where text mining techniques were used for text pre-processing, analysis was carried out with NLP techniques. In 83 of the fake news datasets and 91 of the overall news datasets considered in the study, negative emotion was more dominant than other emotions, and it was observed that as negative comments increased, fake news spread more as well as real news. While neutral comments have no effect on prevalence, users who comment on fake news for fun significantly increase the prevalence. Finally, to reveal bot activity NLP techniques were applied.

 The use of social media as a news source is quite common today. However, the fact that the news encountered on social media are accepted as true without questioning or checking their validity is one of the main reasons for the dissemination of fake news. For the social media ecosystem, the question arises as to which emotion is more effective in spreading fake news, as the accuracy and validity of the news are under the control of opinions and emotions rather than evidence-based data. From this point of view, our study investigates whether there is a relationship between users reaction to the news and the prevalence of the news. In our study, sentiment analysis was conducted on the reactions of Twitter users to fake news about the COVID-19 vaccine between December 31, 2019 and July 30, 2022. To fully assess whether there is a relationship between the reactions and the prevalence of the news, the spread of real news published in the same period in addition to fake news is also taken into consideration. Fake and real news comments, which were selected in different degrees of prevalence from the most to the least, were examined comparatively. In the study, where text mining techniques were used for text pre-processing, analysis was carried out with NLP techniques. In 83 of the fake news datasets and 91 of the overall news datasets considered in the study, negative emotion was more dominant than other emotions, and it was observed that as negative comments increased, fake news spread more as well as real news. While neutral comments have no effect on prevalence, users who comment on fake news for fun significantly increase the prevalence. Finally, to reveal bot activity NLP techniques were applied.

 The use of social media as a news source is quite common today. However, the fact that the news encountered on social media are accepted as true without questioning or checking their validity is one of the main reasons for the dissemination of fake news. For the social media ecosystem, the question arises as to which emotion is more effective in spreading fake news, as the accuracy and validity of the news are under the control of opinions and emotions rather than evidence-based data. From this point of view, our study investigates whether there is a relationship between users reaction to the news and the prevalence of the news. In our study, sentiment analysis was conducted on the reactions of Twitter users to fake news about the COVID-19 vaccine between December 31, 2019 and July 30, 2022. To fully assess whether there is a relationship between the reactions and the prevalence of the news, the spread of real news published in the same period in addition to fake news is also taken into consideration. Fake and real news comments, which were selected in different degrees of prevalence from the most to the least, were examined comparatively. In the study, where text mining techniques were used for text pre-processing, analysis was carried out with NLP techniques. In 83 of the fake news datasets and 91 of the overall news datasets considered in the study, negative emotion was more dominant than other emotions, and it was observed that as negative comments increased, fake news spread more as well as real news. While neutral comments have no effect on prevalence, users who comment on fake news for fun significantly increase the prevalence. Finally, to reveal bot activity NLP techniques were applied.

 The use of social media as a news source is quite common today. However, the fact that the news encountered on social media are accepted as true without questioning or checking their validity is one of the main reasons for the dissemination of fake news. For the social media ecosystem, the question arises as to which emotion is more effective in spreading fake news, as the accuracy and validity of the news are under the control of opinions and emotions rather than evidence-based data. From this point of view, our study investigates whether there is a relationship between users reaction to the news and the prevalence of the news. In our study, sentiment analysis was conducted on the reactions of Twitter users to fake news about the COVID-19 vaccine between December 31, 2019 and July 30, 2022. To fully assess whether there is a relationship between the reactions and the prevalence of the news, the spread of real news published in the same period in addition to fake news is also taken into consideration. Fake and real news comments, which were selected in different degrees of prevalence from the most to the least, were examined comparatively. In the study, where text mining techniques were used for text pre-processing, analysis was carried out with NLP techniques. In 83 of the fake news datasets and 91 of the overall news datasets considered in the study, negative emotion was more dominant than other emotions, and it was observed that as negative comments increased, fake news spread more as well as real news. While neutral comments have no effect on prevalence, users who comment on fake news for fun significantly increase the prevalence. Finally, to reveal bot activity NLP techniques were applied.

Makale detayları

Which Emotions of Social Media Users Lead to Dissemination of Fake News: Sentiment Analysis Towards Covid-19 Vaccine

Yazarlar:

Maide Feyza Er | Yonca Bayrakdar Yılmaz

Yayıncı:

Çanakkale Onsekiz Mart University

Ana Başlıklar:

Artificial Intelligence

Dergi:

Journal of Advanced Research in Natural and Applied Sciences Vol.9 Issue 1, pp.107-126

Belge Tipi:

Makale

Yayın Tarihi:

6/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001284617

pISSN:

2757-5195

Bot detection

fake news

nlp

sentiment analysis

text mining

Sayı

Makale detayları

Which Emotions of Social Media Users Lead to Dissemination of Fake News: Sentiment Analysis Towards Covid-19 Vaccine

Yazarlar: Maide Feyza Er | Yonca Bayrakdar Yılmaz

Yayıncı: Çanakkale Onsekiz Mart University

Ana Başlıklar: Artificial Intelligence

Dergi: Journal of Advanced Research in Natural and Applied Sciences Vol.9 Issue 1, pp.107-126

Belge Tipi: Makale

Yayın Tarihi: 6/2023

Belge Dili: İngilizce

Document ID (Org No.): 2001284617

pISSN: 2757-5195

Bot detection

fake news

nlp

sentiment analysis

text mining

Sayı

Yazarlar:

Maide Feyza Er | Yonca Bayrakdar Yılmaz

Yayıncı:

Çanakkale Onsekiz Mart University

Ana Başlıklar:

Artificial Intelligence

Dergi:

Journal of Advanced Research in Natural and Applied Sciences Vol.9 Issue 1, pp.107-126

Belge Tipi:

Makale

Yayın Tarihi:

6/2023

Belge Dili:

İngilizce

Document ID (Org No.):

2001284617

pISSN:

2757-5195