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Title: :  DETECTING FAKE NEWS THROUGH LOGESTIC REGRESSION
PaperId: :  21642
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 5 2023
DUI:    16.0415/IJARIIE-21642
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Alan JoyKKMMPTC Mala, Kerala, India
M G AlwinKKMMPTC Mala, Kerala, India
Prabath A SKKMMPTC Mala, Kerala, India
Sanjay P SKKMMPTC Mala, Kerala, India
Vinay Krishna C SKKMMPTC Mala, Kerala, India
Sana ShafiKKMMPTC Mala, Kerala, India
Ajith P JKKMMPTC Mala, Kerala, India
Bindu AntoKKMMPTC Mala, Kerala, India

Abstract

Computer Engineering
Fake news, misinformation, logistic regression, natural language processing, naïve baye etc….
When people are exposed to fake news, they might believe false information. This can lead to misguided beliefs and actions based on inaccurate data, affecting their decision-making in areas such as health, politics, and finance. Fake news can shape public opinion and influence elections, policies, and social attitudes. It can sway people’s views on important issues and contribute to polarization in society. Fake news often promotes divisive narratives, fostering hostility and division among different groups of people. This can lead to social unrest and conflicts. False information can influence stock markets, consumer behavior, and investment decisions, potentially causing financial losses for individuals and businesses. In the context of health, fake news can be particularly harmful. We use logestic regression algorithm. Logistic regression is a statistical method used for binary classification tasks, where the goal is to predict one of two possible outcomes, typically labeled as 0 and 1. It’s a type of regression analysis that models the probability of the binary outcome. Logistic regression is widely used in various fields, including healthcare (predicting disease outcomes), marketing (customer churn prediction), and natural language processing (spam detection), among others. It’s a fundamental algorithm in machine learning and serves as a building block for more complex models. This literature review also includes papers discussing algorithms for fake news detection, such as logstic regression, natural language processing and naïve baye Classifier.

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IJARIIE Alan Joy, M G Alwin, Prabath A S, Sanjay P S, Vinay Krishna C S, Sana Shafi, Ajith P J, and Bindu Anto. "DETECTING FAKE NEWS THROUGH LOGESTIC REGRESSION" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 5 2023 Page 535-540
MLA Alan Joy, M G Alwin, Prabath A S, Sanjay P S, Vinay Krishna C S, Sana Shafi, Ajith P J, and Bindu Anto. "DETECTING FAKE NEWS THROUGH LOGESTIC REGRESSION." International Journal Of Advance Research And Innovative Ideas In Education 9.5(2023) : 535-540.
APA Alan Joy, M G Alwin, Prabath A S, Sanjay P S, Vinay Krishna C S, Sana Shafi, Ajith P J, & Bindu Anto. (2023). DETECTING FAKE NEWS THROUGH LOGESTIC REGRESSION. International Journal Of Advance Research And Innovative Ideas In Education, 9(5), 535-540.
Chicago Alan Joy, M G Alwin, Prabath A S, Sanjay P S, Vinay Krishna C S, Sana Shafi, Ajith P J, and Bindu Anto. "DETECTING FAKE NEWS THROUGH LOGESTIC REGRESSION." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 5 (2023) : 535-540.
Oxford Alan Joy, M G Alwin, Prabath A S, Sanjay P S, Vinay Krishna C S, Sana Shafi, Ajith P J, and Bindu Anto. 'DETECTING FAKE NEWS THROUGH LOGESTIC REGRESSION', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 5, 2023, p. 535-540. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/DETECTING_FAKE_NEWS_THROUGH_LOGESTIC_REGRESSION_ijariie21642.pdf (Accessed : ).
Harvard Alan Joy, M G Alwin, Prabath A S, Sanjay P S, Vinay Krishna C S, Sana Shafi, Ajith P J, and Bindu Anto. (2023) 'DETECTING FAKE NEWS THROUGH LOGESTIC REGRESSION', International Journal Of Advance Research And Innovative Ideas In Education, 9(5), pp. 535-540IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/DETECTING_FAKE_NEWS_THROUGH_LOGESTIC_REGRESSION_ijariie21642.pdf (Accessed : )
IEEE Alan Joy, M G Alwin, Prabath A S, Sanjay P S, Vinay Krishna C S, Sana Shafi, Ajith P J, and Bindu Anto, "DETECTING FAKE NEWS THROUGH LOGESTIC REGRESSION," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 5, pp. 535-540, Sep-Oct 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/DETECTING_FAKE_NEWS_THROUGH_LOGESTIC_REGRESSION_ijariie21642.pdf [Accessed : ].
Turabian Alan Joy, M G Alwin, Prabath A S, Sanjay P S, Vinay Krishna C S, Sana Shafi, Ajith P J, and Bindu Anto. "DETECTING FAKE NEWS THROUGH LOGESTIC REGRESSION." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 5 ().
Vancouver Alan Joy, M G Alwin, Prabath A S, Sanjay P S, Vinay Krishna C S, Sana Shafi, Ajith P J, and Bindu Anto. DETECTING FAKE NEWS THROUGH LOGESTIC REGRESSION. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : ]; 9(5) : 535-540. Available from: https://ijariie.com/AdminUploadPdf/DETECTING_FAKE_NEWS_THROUGH_LOGESTIC_REGRESSION_ijariie21642.pdf
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