Fraud Detection of Facebook Business Page Based on Sentiment Analysis

Nasrin, Samia; Ghosh, Priyanka; Chowdhury, S. M. Mazharul Hoque; Abujar, Sheikh; Hossain, Syed Akhter

doi:10.1007/978-981-13-7564-4_25

Cited by 5 publications

(6 citation statements)

References 8 publications

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“…In 2019 study [7] used the Naïve Bayes and lexicon-based methods to detect hoaxes based on sentiment analysis on Facebook business pages. Where all comments for each post will be analyzed for sentiment, then all posts with a percentage of positive comments lower than 65% will proceed to the hoax detection process.…”

Section: A Related Workmentioning

confidence: 99%

“…Each word that has similarities with the word dictionary will get one point. Based on this, equations can be made, such as [7]:…”

Section: E Hoax Tweet Detectionmentioning

confidence: 99%

mentioning

confidence: 99%

“…In the study [7], hoax detection was based on sentiment analysis with the Naïve Bayes algorithm and lexicon-based analysis. In the study [7], the method used to detect hoaxes is double-checking post comments on Facebook business pages. Where all comments for each post will be analyzed for sentiment, then will proceed to the hoax detection process.…”

mentioning

confidence: 99%

“…Based on the previous explanation, in this research, the author will detect hoaxes in tweets crawled from Twitter based on sentiment analysis with the Support Vector Machine algorithm. Different from the study [7], in this research, the hoax detection process will be focused on checking post tweets, not the tweet replies/comments. In this study, there are two different tasks, the first task is sentiment analysis of tweet replies, and the second task is hoax detection of post tweets.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Hoax COVID-19 News Detection Based on Sentiment Analysis in Indonesian using Support Vector Machine (SVM) Method

Shafira

2023

ijoict

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The increasing use of technology makes it easier for information media such as news to be disseminated and does not demand possibilities, there is a lot of hoax news spreading. Twitter is one of the media most frequently used by the public to access and disseminate information. This research will focus on detecting Indonesian language COVID-19 news taken from Twitter. Detection of hoax news can be assisted by using sentiment analysis, one of the uses of classification text. Support Vector Machine (SVM) can be used to perform sentiment analysis tasks. After getting the sentiment analysis results, the hoax detection process will use the Bag of Words. Bag of Words is a collection of word dictionaries for weighting words to determine specific labels. The built SVM model succeeded in classifying tweet repliessentiment with an average accuracy of 83.17% with a threshold of 35%. At the same time, the hoax detection process gets the best accuracy of 62.5% with a threshold of -5 or -6.

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Section: A Related Workmentioning

confidence: 99%

“…Each word that has similarities with the word dictionary will get one point. Based on this, equations can be made, such as [7]:…”

Section: E Hoax Tweet Detectionmentioning

confidence: 99%

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confidence: 99%

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confidence: 99%

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confidence: 99%