Topic Modeling as a Tool to Gauge Political Sentiments from Twitter Feeds

Sarddar, Debabrata; Dey, Raktim Kumar; Bose, Rajesh; Roy, Sandip

doi:10.4018/ijncr.2020040102

Cited by 9 publications

(3 citation statements)

References 20 publications

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“…Emerging technologies provide great health communication opportunities, particularly through video-based platforms [ 10 , 11 , 12 , 13 , 14 ]. TikTok is an online video platform where users can post a short, 30 s video.…”

Section: Introductionmentioning

confidence: 99%

Reliability, Quality, and Educational Suitability of TikTok Videos as a Source of Information about Scoliosis Exercises: A Cross-Sectional Study

et al. 2022

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This study aimed to systematically assess the informational reliability, quality, and educational suitability of videos introducing scoliosis exercises on TikTok. We retrieved and screened 1904 TikTok videos with the hashtags: “#scoliosis”, “#scoliosisexercise”, and “#scoliosistips”, before collecting a final sample of 171 scoliosis exercises in March 2022. Then, two independent raters assessed the reliability and quality of the videos using the DISCERN instrument and evaluated the educational suitability of the information using “Scoliosis Exercise Education Score” (SEES; exercise cycle, target, effect, precaution, and rationale). None of the videos were rated as excellent or good according to DISCERN. The mean SEES score was 2.02 out of 5. Videos uploaded by health organizations had significantly lower DISCERN and SEES scores than those by general users and healthcare professionals. Regarding the propriety of physiotherapeutic scoliosis-specific exercises (PSSE), DISCERN and SEES scores were significantly higher in the PSSE proper group than in the PSSE non-proper group. Although TikTok has become a popular source of scoliosis-related information, the overall information quality, reliability, and educational suitability of videos on scoliosis exercises in TikTok appear to be low, suggesting that TikTok is not suitable source for obtaining scoliosis exercise information.

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Section: Introductionmentioning

confidence: 99%

Reliability, Quality, and Educational Suitability of TikTok Videos as a Source of Information about Scoliosis Exercises: A Cross-Sectional Study

et al. 2022

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“…Twitter is actively used for political discourse. Twitter users tend to discuss common political concerns and interests on Twitter (Sarddar et al, 2020). According to Sarddar et al (2020), elections in Canada, the US, and overseas have widely used Twitter for political discourse.…”

Section: Twitter and Politicsmentioning

confidence: 99%

The Drivers of Polarity in Sentiments on Social Media: an Exploratory Study on the 2021 Canadian Federal Election

Noor

2024

Preprint

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<p>The drivers of polarity in sentiments on social media - an exploratory study on the 2021 Canadian Federal Election Hiba Mohammad Noor Master of Science in Management, 2022 Master of Science in Management, Ryerson University Social media is used by the public, voters, and politicians to share their political opinions leading to online political discourse. The opinions shared by voters on social media have different sentiments associated with them depending on voter needs and priorities. Understanding the factors that drive these sentiments can help policymakers and other political stakeholders to understand voter needs and expectations and develop policies that align with those needs. This research focuses on identifying the factors (keywords) that drive these sentiments. This research also investigates the relationship between these keywords and the number of retweets and hashtags. Sentiment analysis was performed on 779,169 tweets related to the 2021 Canadian Federal election followed by text clustering and keywords analysis. The topics and keywords that drive the sentiments were identified. Chi-Square test was used to investigate the relationship between these keywords, hashtags, and the number of retweets. The results suggest that some keywords are common in opposite sentiment types (positive and negative) which shows polarization in Twitter and some keywords are unique to a sentiment type which shows that these keywords drive that specific sentiment. The results also suggest that there is no significant relationship between the keywords and the number of hashtags but has a significant relationship between the keywords and the number of retweets for extremely negative tweets only. </p>

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“…NLP has spawned a slew of new applications. A chatbot is one of the most intriguing natural language artificial intelligence applications [4]. A chatbot is software that uses natural language to conduct a human-computer interaction through auditory or textual means.…”

Section: Introductionmentioning

confidence: 99%

ArRASA: Channel Optimization for Deep Learning-Based Arabic NLU Chatbot Framework

Alruily

2022

Electronics

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Since the introduction of deep learning-based chatbots for knowledge services, many research and development efforts have been undertaken in a variety of fields. The global market for chatbots has grown dramatically as a result of strong demand. Nevertheless, open-domain chatbots’ limited functional scalability poses a challenge to their implementation in industries. Much work has been performed on creating chatbots for languages such as English, Chinese, etc. Still, there is a need to develop chatbots for other languages such as Arabic, Persian, etc., as they are widely used on the Internet today. In this paper, we introduce, ArRASA as a channel optimization strategy based on a deep-learning platform to create a chatbot that understands Arabic. ArRASA is a closed-domain chatbot that can be used in any Arabic industry. The proposed system consists of four major parts. These parts include tokenization of text, featurization, intent categorization and entity extraction. The performance of ArRASA is evaluated using traditional assessment metrics, i.e., accuracy and F1 score for the intent classification and entity extraction tasks in the Arabic language. The proposed framework archives promising results by securing 96%, 94% and 94%, 95% accuracy and an F1 score for intent classification and entity extraction, respectively.

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Topic Modeling as a Tool to Gauge Political Sentiments from Twitter Feeds

Cited by 9 publications

References 20 publications

Reliability, Quality, and Educational Suitability of TikTok Videos as a Source of Information about Scoliosis Exercises: A Cross-Sectional Study

Reliability, Quality, and Educational Suitability of TikTok Videos as a Source of Information about Scoliosis Exercises: A Cross-Sectional Study

The Drivers of Polarity in Sentiments on Social Media: an Exploratory Study on the 2021 Canadian Federal Election

ArRASA: Channel Optimization for Deep Learning-Based Arabic NLU Chatbot Framework

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