Notes

Classification of Arabic Tweets: A Review - MDPI

<h1 style="clear:both" id="content-section-0">Not known Facts About Catholic publication's Twitter account locked over tweet about<br></h1>
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<img width="464" src="https://ezmarketingsecrets.com/wp-content/uploads/2021/06/TweetX-Review.png">
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<p class="p__0">Self-Produced Belief Analysis Tools, Of the 12 research studies evaluated, 6 produced sentiment analysis tools within their own department, particularly designed for their research study using currently defined algorithms. Liu explains the various kinds of algorithms that can be utilized, and they produce different sort of summaries [,] Moreover, 2 various types of algorithms were discovered to be used, a basic monitored machine finding out algorithm and a classification method (such as AFINN called after the author, Finn Arup Neilsen).</p>
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<img class="featurable" style="max-height:300px;max-width:400px;" itemprop="image" src="https://c.ndtvimg.com/2021-06/00cudnv_yogi-650_625x300_02_June_21.jpg" alt="Will Twitter's 'Review Your Tweet' Prompt Affect User's Behaviour?"><span style="display:none" itemprop="caption">Twitter Style Book Review Lesson</span>
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<p class="p__1">These may be different from the open source tools, which use currently pretrained classifiers in premade software systems designed more towards an end user. Related Source Here of 3 documents used a comparable method of belief through classification, all taking a look at opinions towards smoking. Sofean et al produced an automatic sentiment tool based on identifying 250 favorable and 250 negative tweets from a smaller sample to train their tool []</p>
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<h1 style="clear:both" id="content-section-1">4 Simple Techniques For Twitter Prompts Users to Check for 'Offensive' Content Before<br></h1>
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<p class="p__2">A restriction to their tool was that it screened out emoticons (signs utilized to reveal feeling) prior to producing a tool. This is a method frequently utilized by users to communicate feeling [] Myslin et al analyzed the belief toward emerging tobacco products on 7362 tweets, where Cole-Lewis et al looked particularly at belief towards electric cigarettes on 17,098 tweets [,]</p>
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<p class="p__3">Tweets were broadly categorized into "favorable," "neutral," or "negative" by the annotators. The strength of the belief was not recorded. To discover the relationship in between the sentiment and topic, 3 artificial intelligence algorithms were used, Nave Bayes, K-Nearest-Neighbor, and Support Vector Maker [] An automated belief analysis tool was produced based on the manual analysis of belief of a sample of tweets during the pilot stage of each research study.</p>
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<img class="featurable" style="max-height:300px;max-width:400px;" itemprop="image" src="https://www.thehindubusinessline.com/info-tech/social-media/man6tv/article33910947.ece/ALTERNATES/LANDSCAPE_355/Bl-twitter" alt="Tweet Cute by Emma Lord [review] oh yeah, and I'm also back from my hiatus (temporarily?) – Paper Blots"><span style="display:none" itemprop="caption">Twitter Lets You Review Offensive Tweets Before Sending - HYPEBEAST</span>
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<img class="featurable" style="max-height:300px;max-width:400px;" itemprop="image" src="https://www.theparisreview.org/blog/wp-content/uploads/2014/01/Lockwood-Tweet.jpg" alt="Twitter relaunches prompt that asks users to review potentially harmful or offensive tweets on iOS - The Hindu BusinessLine"><span style="display:none" itemprop="caption">This New App Makes Me $476 Everyday 🔥 TweetX Review, Demo, Bonus 🔥 Make Money Online 2021 - YouTube</span>
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<h2 style="clear:both" id="content-section-2">Things about Sentiment Analysis of - JMIR Public Health and Surveillance<br></h2>
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<p class="p__4">58% (1000/7362) for Myslin. The research study by Cole-Lewis utilized just 1. 46% (250/17,098) of their total sample to train their algorithms. This represents a very small percentage of their sample and might result in their technique being less accurate than planned. However, no remark is made by the study hall to why only this number was utilized.</p>
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