Notes

Classification of Arabic Tweets: A Review - MDPI

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<img class="featurable" style="max-height:300px;max-width:400px;" itemprop="image" src="https://s.wsj.net/public/resources/images/BN-RJ794_1227go_P_20161227181745.jpg" alt="PEUGEOT TWEET 125 (2010-on) Review - Specs &amp; Prices - MCN"><span style="display:none" itemprop="caption">Administration wants Supreme Court to review suit on Trump's Twitter-blocking - POLITICO</span>
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<h1 style="clear:both" id="content-section-0">Not known Factual Statements About Catholic publication's Twitter account locked over tweet about<br></h1>
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<p class="p__0">An overall of 69 full-text articles were assessed for eligibility. Of these, 15% (10/69) were declined since they looked at social networks in basic (not Twitter specifically), for example, using social media by surgical colleagues [] Moreover, 36% (25/69) were rejected because the study did not relate to health care, for instance, public understandings of nonmedical use of opioids []</p>
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<iframe src="https://www.youtube.com/embed/b4rxwyuhHzg" width="560" height="315" frameborder="0" allowfullscreen></iframe>
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<img class="featurable" style="max-height:300px;max-width:400px;" itemprop="image" src="https://www.fanbolt.com/storage/2018/12/Funny-Tweets-570x356.jpg" alt="Uttar Pradesh " review" over, top bjp leader tweets praise for yogi adityanath"><span style="display:none" itemprop="caption">TweetX Review - Imagine being able to crack the traffic “mystery"</span>
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<p class="p__1">The requirements utilized to compare the techniques in each research study took a look at the technique of tool production, in which setting it was utilized, and the approach of evaluating the tool. For assessment, a comparison of the variety of annotators utilized to manually annotate tweets, if any, and the level of arrangement in between them was utilized.</p>
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<p class="p__2">Results, General Results, In overall, 12 documents were discovered that satisfied all 3 inclusion criteria (see for introduction). These were published between 2011 and 2016 with data gathered from Twitter in between 2006 and 2016. Moreover, 2 documents taken a look at global data, 9 in the United States, and 1 in the UK.</p>
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<h1 style="clear:both" id="content-section-1">"#AcademicFreedom: Twitter and First Amendment Rights for for Dummies<br></h1>
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<p class="p__3">Many research studies conducted analysis on public healthrelated subjects (n=7). In addition, 3 papers took a look at the sentiment towards an aspect of disease: the illness itself (n=1), signs (n=1), or treatment (n=1). Lastly, Related Source Here studied an emergency medical situation and a medical conference. An overall of 5 of the 12 studies performed a manual belief analysis of a sample of their data utilizing annotators to train their tool.</p>
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<p class="p__4">58% (1000/7362) of their last data sample to train their developed method [] 3 studies utilized approximately 0. 7% of their total dataset to train their tool (1. 46%, 250/17,098; 0. 55%, 2216/404,065; and 0. 1%, 250/198,499). One paper compared the accuracy of their picked methods with a manually annotated corpus of their data []</p>
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<p class="p__5">There were 3 categories of belief analysis methods discovered (see ), a tool particularly produced and trained for that study information, open source tools, and commercially offered software application. This distinction was made based on the required level of expertise in computer programming needed to implement that approach and if predefined lexicons were used.</p>
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