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Title: :  Filtering sentiment from social media
PaperId: :  7687
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 4 Issue 2 2018
DUI:    16.0415/IJARIIE-7687
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Aher PriyankaPune Vidyarthi Griha's College of Engineering,Nashik
Yerandekar ManishaPune Vidyarthi Griha's College of Engineering,Nashik
Tidme PoojaPune Vidyarthi Griha's College of Engineering,Nashik
Ganjave DeepaliPune Vidyarthi Griha's College of Engineering,Nashik

Abstract

computer engineering
Track post, sentiment analysis, Naïve Bayes algorithm, political words, nonpolitical words,classification, Facebook
Now a days social media is playing a important role in affecting people’s feelings in side or opposite a government or an institution. Therefore, to understand the sentiment of any posting in social media, an effective procedure is necessity. We have analyzed some Facebook postings to understand political sentiments. In any politically infected posting, there are some dominant words. At beginning, we have created a dictionary consisting of unique words gathered from political or nonpolitical posts or comments and then trained using Naïve Bayes algorithm based on probability algorithm. To identify the sentiment expressed in a new post or comment, we have taken each word of the posting and then compared those with the dictionary words for classification. At last, we have tested our algorithm using two hundred postings from Facebook and our result shows that the method can classify posts or comments with good accuracy. The field “political marketing”, although relatively new, has grown quickly over the last few years. Now, it attracts scholars from a number of disciplines outside the mainstream marketing field. Political parties started to use the marketing instruments as their electoral campaigning. The term “Political marketing” contain these activities made by political parties to affect voters and is aimed on affecting the individuals with respect to political candidates to reach the maximum number of vote. One of the marketing instruments that political parties use to reach the voters is the use of social media. Since the increase of the internet in the early 1990s, the world’s networked population has increased from the millions to the billions. Social media have become very important for life for society all over.. As the communications landscape gets more complicated, and more participatory, the networked population is getting much more importance and gaining greater power since social media gives people, the opportunity to access information much more simply, and it also gives more opportunities to engage in public conversation. As a result, it increased the capability of people to undertake collective action. This paper checks the effects of political marketing and specially using social media on voters of the 30 March 2014 local elections in Turkey. At beginning, it reviews the theory of marketing in brief terms and political marketing as part of it. And then, the new and popular social media channels were identified.

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IJARIIE Aher Priyanka, Yerandekar Manisha, Tidme Pooja, and Ganjave Deepali. "Filtering sentiment from social media" International Journal Of Advance Research And Innovative Ideas In Education Volume 4 Issue 2 2018 Page 1162-1168
MLA Aher Priyanka, Yerandekar Manisha, Tidme Pooja, and Ganjave Deepali. "Filtering sentiment from social media." International Journal Of Advance Research And Innovative Ideas In Education 4.2(2018) : 1162-1168.
APA Aher Priyanka, Yerandekar Manisha, Tidme Pooja, & Ganjave Deepali. (2018). Filtering sentiment from social media. International Journal Of Advance Research And Innovative Ideas In Education, 4(2), 1162-1168.
Chicago Aher Priyanka, Yerandekar Manisha, Tidme Pooja, and Ganjave Deepali. "Filtering sentiment from social media." International Journal Of Advance Research And Innovative Ideas In Education 4, no. 2 (2018) : 1162-1168.
Oxford Aher Priyanka, Yerandekar Manisha, Tidme Pooja, and Ganjave Deepali. 'Filtering sentiment from social media', International Journal Of Advance Research And Innovative Ideas In Education, vol. 4, no. 2, 2018, p. 1162-1168. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Filtering_sentiment_from_social_media_ijariie7687.pdf (Accessed : 01 August 2023).
Harvard Aher Priyanka, Yerandekar Manisha, Tidme Pooja, and Ganjave Deepali. (2018) 'Filtering sentiment from social media', International Journal Of Advance Research And Innovative Ideas In Education, 4(2), pp. 1162-1168IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Filtering_sentiment_from_social_media_ijariie7687.pdf (Accessed : 01 August 2023)
IEEE Aher Priyanka, Yerandekar Manisha, Tidme Pooja, and Ganjave Deepali, "Filtering sentiment from social media," International Journal Of Advance Research And Innovative Ideas In Education, vol. 4, no. 2, pp. 1162-1168, Mar-App 2018. [Online]. Available: https://ijariie.com/AdminUploadPdf/Filtering_sentiment_from_social_media_ijariie7687.pdf [Accessed : 01 August 2023].
Turabian Aher Priyanka, Yerandekar Manisha, Tidme Pooja, and Ganjave Deepali. "Filtering sentiment from social media." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 4 number 2 (01 August 2023).
Vancouver Aher Priyanka, Yerandekar Manisha, Tidme Pooja, and Ganjave Deepali. Filtering sentiment from social media. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2018 [Cited : 01 August 2023]; 4(2) : 1162-1168. Available from: https://ijariie.com/AdminUploadPdf/Filtering_sentiment_from_social_media_ijariie7687.pdf
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