Reversing the Polarity with Emoticons

Teh, Phoey Lee; Rayson, Paul; Pak, Irina; Piao, Scott; Yeng, Seow Mei

doi:10.1007/978-3-319-41754-7_48

Cited by 15 publications

(14 citation statements)

References 7 publications

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“…Research in the field of human-computer interaction and natural language processing may lead the way; extant studies find that even text-based communication can communicate emotion through capitalization, emoticons, and repetition. [38][39][40][41] With virtual and augmented reality becoming increasingly sophisticated, the likelihood that children will learn from these technologies is high. 42 Digital media and technology are increasingly used in classrooms and at home; as such, this kind of inquiry is essential as we look to support our species in an increasingly mediated world.…”

Section: Future Directions and Implicationsmentioning

confidence: 99%

Mobile Technologies and Their Relationship to Children's Ability to Read Nonverbal Emotional Cues: A Cross-Temporal Comparison

Uhls

Broome

Levi

et al. 2020

Cyberpsychology, Behavior, and Social Networking

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Key social learning occurs during early childhood with lasting effects throughout the lifespan. In the past 10 years, ownership of mobile technology grew rapidly, particularly in households with young children; this has dramatically changed the early learning landscape. With the ubiquity of mobile devices, many have questioned their effect on the social and emotional learning of children. To explore one aspect of this question, we conducted a crosstemporal comparison to compare two cohorts of sixth graders, one measured in 2012 and another in 2017. Each group took tests, one with still photographs of faces (diagnostic analysis of nonverbal accuracy 2 or DANVA2) and one with videotaped vignettes (the child and adolescent social perception measure or CASP), designed to measure their ability to accurately identify nonverbal emotional cues. We sought to explore whether changes in the early learning environment of the 2017 cohort, who grew up with mobile phones and tablets, could be related to participants' ability to read nonverbal emotional cues. We found that sixth-grade students in 2017 performed better than sixth-grade students in 2012 on the DANVA2, but not on the CASP. One possible reason participants improved on the test with still photographs is because mediated communication has become more visual and less text based, and sharing photographs of oneself and others is more common. Accordingly participants may be more accurate at interpreting emotional cues in photographs due to a larger exposure to photographs of faces.

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Section: Future Directions and Implicationsmentioning

confidence: 99%

Mobile Technologies and Their Relationship to Children's Ability to Read Nonverbal Emotional Cues: A Cross-Temporal Comparison

Uhls

Broome

Levi

et al. 2020

Cyberpsychology, Behavior, and Social Networking

View full text Add to dashboard Cite

show abstract

“…PELESent's approach to label data is fast, but is unable to deal with several language phenomena as irony and sarcasm, that can lead to incorrect labeling. Indeed some research, as [7], has found that emoticons are able to reverse the polarity of the true sentiment values of sentences. For our experiments we choose to use BRTweetSentCorpus as it covers a broader set of topics than TweetSentBR.…”

Section: Datasets For Brazilian Portuguese Sentiment Analysismentioning

confidence: 99%

Sentiment Analysis of Tweets in Brazilian Portuguese with Convolutional Neural Networks

Coello

Neto

2019

Int J Innov Educ Res

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Sentiment analysis of texts posted on Twitter is a natural language processing task whose importance has grown along with the increase in the number of users of the platform and the interest of organizations on the opinions of their employees, customers and users.Although Brazil is the sixth country in the world with most active users of Tweeter and Portuguese is the seventh most spoken language in the world, with 221 million speakers (200 million of them living in Brazil), the number of articles that discuss sentiment analysis approaches for Brazilian Portuguese is a small fraction of those that focus on the English language. On the other hand, few works use deep learning for this task when compared with other machine learning and lexical based methods. In this context, the work described in this article addresses the problem using Convolutional Neural Networks (CNN). The paper presents the results of an experimental evaluation that shows that a CNN with a relatively simple architecture can perform much better than a previous approach that uses ensembles of other machine learning classifiers combined with text preprocessing heuristics

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“…Researchers revealed that emoticons are not just for fun, in fact, they serve as an additional and valuable supplement in communication methods (Huang, Yen, & Zhang, 2008). In addition, the latest study by Teh, Rayson, Pak, Piao, and Yeng (2016) discovered that emoticons have significant abilities to reverse the polarity of comments. It further corroborates that the processing and understanding of emotions expressed by the comments is vitally important in sentiment analysis and studies.…”

Section: Related Workmentioning

confidence: 99%

Consistency of Online Consumers’ Perceptions of Posted Comments: An Analysis of Tripadvisor Reviews

Khoo

Teh

Ooi

2017

JICT

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Ratings and comments play a dominant role in online reviews. The question, thus, arises as to whether or not there is any consistency in consumer perception of the reviews, and how future choices might be influenced. We analysed 2000 comments of 20 different hotels posted on TripAdvisor to determine if the comments posted by previous guests of a hotel influence the decisions of potential guests. Two hundred human raters were asked to consider 20 reviews and to rate a hotel based on the reviews. The Cohen Kappa coefficient was used to evaluate the degree of agreement on the hotel quality as determined by the human raters and the star rating given by the original reviewer. The results showed a high consistency between the human raters' evaluation and the reviewers' star rating. This research reveals the importance of website feedback such as TripAdvisor in influencing consumer choice.

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Reversing the Polarity with Emoticons

Cited by 15 publications

References 7 publications

Mobile Technologies and Their Relationship to Children's Ability to Read Nonverbal Emotional Cues: A Cross-Temporal Comparison

Mobile Technologies and Their Relationship to Children's Ability to Read Nonverbal Emotional Cues: A Cross-Temporal Comparison

Sentiment Analysis of Tweets in Brazilian Portuguese with Convolutional Neural Networks

Consistency of Online Consumers’ Perceptions of Posted Comments: An Analysis of Tripadvisor Reviews

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