Context Prediction in the Social Web Using Applied Machine Learning: A Study of Canadian Tweeters

Samuel, Hamman; Noori, Benyamin; Farazi, Sara; Zaı̈ane, Osmar R.

doi:10.1109/wi.2018.00-85

Cited by 4 publications

(3 citation statements)

References 12 publications

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“…As an example, one study in the review made use of a random forest classifier to predict which city and province a tweet determined to be from Canada (according to the Twitter API), was from Ref. [105]. While geographic identification in itself is not of major use to the field of public health, when combined with other identified public health research domains, it offers improvements on the specificity and granularity of their results.…”

Section: Geographic Identificationmentioning

confidence: 99%

A scoping review of the use of Twitter for public health research

Edo-Osagie

Iglesia

Lake

et al. 2020

Computers in Biology and Medicine

120

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Public health practitioners and researchers have used traditional medical databases to study and understand public health for a long time. Recently, social media data, particularly Twitter, has seen some use for public health purposes. Every large technological development in history has had an impact on the behaviour of society. The advent of the internet and social media is no different. Social media creates public streams of communication, and scientists are starting to understand that such data can provide some level of access into the people's opinions and situations. As such, this paper aims to review and synthesize the literature on Twitter applications for public health, highlighting current research and products in practice. A scoping review methodology was employed and four leading health, computer science and cross-disciplinary databases were searched. A total of 755 articles were retreived, 92 of which met the criteria for review. From the reviewed literature, six domains for the application of Twitter to public health were identified: (i) Surveillance; (ii) Event Detection; (iii) Pharmacovigilance; (iv) Forecasting; (v) Disease Tracking; and (vi) Geographic Identification. From our review, we were able to obtain a clear picture of the use of Twitter for public health. We gained insights into interesting observations such as how the popularity of different domains changed with time, the diseases and conditions studied and the different approaches to understanding each disease, which algorithms and techniques were popular with each domain, and more.

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Section: Geographic Identificationmentioning

confidence: 99%

A scoping review of the use of Twitter for public health research

Edo-Osagie

Iglesia

Lake

et al. 2020

Computers in Biology and Medicine

120

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“…A total of 150 tweets (including retweets posted by the organization) reflecting the pandemic-related context were analyzed using the content analysis approach (Vaismoradi et al 2013;Weber 1990). These tweets were drawn from a large pool of tweets collected by the Grebe Social Media Aggregator (Samuel et al 2018). The coding of tweets was done by a single reviewer, and was inspired by the work of various authors such as Aharony ( 2010), Shiri andAl-Daihani andAlAwadhi (2015).…”

Section: Methodsmentioning

confidence: 99%

Use of Twitter by a Public Library During the Pandemic

Rathi¹

2021

CAIS/ACSI

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Social media such as Twitter and Facebook are used by organizations including public libraries to disseminate a variety of information to community members. This research aims to identify key areas in which Twitter was used to share information with users during the initial pandemic phase by a large public library operating in the Western region of Canada. The findings resulting from the analysis of 150 tweets revealed that the library shared information primarily in the following areas: Programs and Services, Library Operations, Health and Hygiene, Resources, and Other.

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“…Tweets were gathered using the Grebe open source social data aggregation platform [25]. Grebe allows indexing of real-time tweets with a specified geo-fence, as well as direct querying of the Twitter API for retrieval of tweets with applied filters.…”

Section: Platform For Retrieval Of Tweetsmentioning

confidence: 99%

Effects of the COVID-19 Pandemic on Classrooms: A Case Study on Foreigners in South Korea Using Applied Machine Learning

2021

Self Cite

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In this study, we qualitatively and quantitatively examine the effects of COVID-19 on classrooms, students, and educators. Using a new Twitter dataset specific to South Korea during the pandemic, we sample the sentiment and strain on students and educators using applied machine learning techniques in order to identify various topical pain points emerging during the pandemic. Our contributions include a novel and open source geo-fenced dataset on student and educator opinion within South Korea that we are making available to other researchers as well. We also identify trends in sentiment and polarity over the pandemic timeline, as well as key drivers behind the sentiments. Moreover, we provide a comparative analysis of two widely used pre-trained sentiment analysis approaches with TextBlob and VADER using statistical significance tests. Ultimately, we analyze how public opinion shifted on the pandemic in terms of positive sentiments about accessing course materials, online support communities, access to classes, and creativity, to negative sentiments about mental fatigue, job loss, student concerns, and overwhelmed institutions. We also initiate initial discussions about the concept of actionable sentiment analysis by overlapping polarity with the concept of trigger management to assist users in coping with negative emotions. We hope that insights from this preliminary study can promote further utilization of social media datasets to evaluate government messaging, population sentiment, and multi-dimensional analysis of pandemics.

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Context Prediction in the Social Web Using Applied Machine Learning: A Study of Canadian Tweeters

Cited by 4 publications

References 12 publications

A scoping review of the use of Twitter for public health research

A scoping review of the use of Twitter for public health research

Use of Twitter by a Public Library During the Pandemic

Effects of the COVID-19 Pandemic on Classrooms: A Case Study on Foreigners in South Korea Using Applied Machine Learning

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