Social Media Discussion Forums Research Articles

Fine grained irony classification through transfer learning approach

Nowadays irony appears to be pervasive in all social media discussion forums and chats, offering further obstacles to sentiment analysis efforts. The aim of the present research work is to detect irony and its types in English tweets We employed a new system for irony detection in English tweets, and we propose a distilled bidirectional encoder representations from transformers (DistilBERT)light transformer model based on the bidirectional encoder representations from transformers (BERT) architecture, this is further strengthened by the use and design of bidirectional long-short term memory (Bi-LSTM) network this configuration minimizes data preprocessing tasks proposed model tests on a SemEval-2018 task 3, 3,834 samples were provided. Experiment results show the proposed system has achieved a precision of 81% for not irony class and 66% for irony class, recall of 77% for not irony and 72% for irony, and F1 score of 79% for not irony and 69% for irony class since researchers have come up with a binary classification model, in this study we have extended our work for multiclass classification of irony. It is significant and will serve as a foundation for future research on different types of irony in tweets.

Fine grained irony classification through transfer learning approach

Nowadays irony appears to be pervasive in all social media discussion forums and chats, offering further obstacles to sentiment analysis efforts. The aim of the present research work is to detect irony and its types in English tweets We employed a new system for irony detection in English tweets, and we propose a distilled bidirectional encoder representations from transformers (DistilBERT) light transformer model based on the bidirectional encoder representations from transformers (BERT) architecture, this is further strengthened by the use and design of bidirectional long-short term memory (Bi-LSTM) network this configuration minimizes data preprocessing tasks proposed model tests on a SemEval2018 task 3, 3,834 samples were provided. Experiment results show the proposed system has achieved a precision of 81% for not irony class and 66% for irony class, recall of 77% for not irony and 72% for irony, and F1 score of 79% for not irony and 69% for irony class since researchers have come up with a binary classification model, in this study we have extended our work for multiclass classification of irony. It is significant and will serve as a foundation for future research on different types of irony in tweets.

Social media discussion forums, home country and immigrant consumer acculturation: the case of Iranian immigrants in Australia

PurposeSocial media has transformed communication possibilities for immigrant consumers with their home country in their acculturation efforts. However, the acculturative outcomes of consumer interactions with the home country through social media are largely overlooked in previous research. This study aims to investigate the acculturative processes and outcomes resulting from interacting with the home country through social media.Design/methodology/approachA netnographic approach is used to collect data from a social media platform that provides an interactive social context in which Iranian immigrants in Australia share their experiences of immigration with non-immigrants who are considering and planning to migrate to Australia.FindingsFindings show how both immigrants and non-immigrant users via social media reflexively contribute to the formation of two competing collective narratives, namely, the dominant, romanticizing narrative and counter, pragmatic narratives. Findings highlight how notions of the home and host countries, and the idea of migrating from home to host, are constructed as the result of the circulation of the dominant and counter narratives. Further findings include how these two collective narratives come into play in the formation of three acculturative outcomes, namely, self-validating, ordinary experts and wellbeing. These insights extend consumer acculturation theory through highlighting the acculturative processes and outcomes of interactions with the home country via a social media platform. This includes, for example, how interacting with the home culture can take on assimilationist properties through the construction of a romanticized representation of the hosting society (i.e. Australia) in the dominant collective narrative.Practical implicationsImplications for ethnic marketing practice, policymakers and non-governmental organisations are advanced, especially regarding using social media as a channel to communicate with current and potential immigrant consumers. Notably, policymakers can use social media to engage with immigrants before and after migration to reduce the potential for cognitive dissonance in recent arrivals. Managerially, brands can advertise on Web-based forums, independent websites and social media platforms to target potential immigrants to sell relevant products immigrants needs after migrating to the host country.Social implicationsFindings broaden the understanding of the potential acculturative outcomes on social media by moving away from the traditional outcomes, which are restricted to the dichotomy between the home and host cultures.Originality/valueScholarly attention is deficient on the role of direct interaction with the home country in immigrant consumer acculturation, especially through social media, which is the focus of this study.

A transformer-based approach to irony and sarcasm detection

Figurative language (FL) seems ubiquitous in all social media discussion forums and chats, posing extra challenges to sentiment analysis endeavors. Identification of FL schemas in short texts remains largely an unresolved issue in the broader field of natural language processing, mainly due to their contradictory and metaphorical meaning content. The main FL expression forms are sarcasm, irony and metaphor. In the present paper, we employ advanced deep learning methodologies to tackle the problem of identifying the aforementioned FL forms. Significantly extending our previous work (Potamias et al., in: International conference on engineering applications of neural networks, Springer, Berlin, pp 164–175, 2019), we propose a neural network methodology that builds on a recently proposed pre-trained transformer-based network architecture which is further enhanced with the employment and devise of a recurrent convolutional neural network. With this setup, data preprocessing is kept in minimum. The performance of the devised hybrid neural architecture is tested on four benchmark datasets, and contrasted with other relevant state-of-the-art methodologies and systems. Results demonstrate that the proposed methodology achieves state-of-the-art performance under all benchmark datasets, outperforming, even by a large margin, all other methodologies and published studies.

Lay perspectives on social distancing and other official recommendations and regulations in the time of COVID-19: a qualitative study of social media posts

BackgroundCOVID-19 caused by a new form of coronavirus (SARS-CoV-2) first appeared in China end of 2019 and quickly spread to all counties of the world. To slow down the spread of the virus and to limit the pressure on the health care systems, different regulations and recommendations have been implemented by authorities, comprising amongst others the closure of all entertainment venues and social distancing. These measures have received mixed reactions, particularly from young individuals, with many not following available advice. Drawing on the information in social media discussion forums, the present study explores the reasons why people ignore the orders and recommendations of the authorities and why the authorities are unable to produce a shared sense of inclusion concerning protective measures against the COVID-19 outbreak.MethodsThree open-access social media forums (Reddit, Twitter, and YouTube comments) were systematically searched with respect to COVID-19-related beliefs, attitudes, and behaviours of individuals. The data was retrieved in the first 3 weeks of March 2020. Qualitative document analysis and qualitative content analysis were used as the methodical approach. The data was reviewed by all authors and jointly interpreted to minimise inconsistencies.ResultsThe study reveals that reasons such as information pollution on social media, the persistence of uncertainty about the rapidly spreading virus, the impact of the social environment on the individual, and fear of unemployment associated with inequality in the distribution of income lead people to ignore the orders and recommendations of the authorities. The findings suggest that government representatives and politicians could not produce a shared sense of inclusion concerning protective measures against the COVID-19 outbreak, due to not building trust among the public and taking concrete economic steps to satisfy them.ConclusionIn uncertain crises, transparency in the presentation of information and government policies emerge as influential determinants in creating social susceptibility and solidarity. The differences between social classes constitute one of the important factors that affect the decision-making mechanisms of individuals in determining the necessary steps to be undertaken in times of crisis.

Shifting from classic learning environment to digital learning environment in Arab culture

Social media discussion forums, blogs, wikis and three-dimensional virtual worlds are the current new techniques for learning. External social media sites, including Facebook (Facebook, Inc., Menlo Park, CA, USA), YouTube (YouTube, LLC, San Bruno, CA, USA), Wikipedia (Wikimedia Foundation, Inc., San Francisco, CA, USA), Flickr (Yahoo Inc., Sunnyvale, CA, USA), Twitter (Twitter, Inc., San Francisco, CA, USA), LinkedIn (LinkedIn, Mountain View, CA, USA) and Second Life (Linden Lab, San Francisco, CA, USA), have been considered as very useful learning and teaching tools in recent years. This provides a chance for student-centred and social constructivist pedagogies in an online environment, and enables students to easily contribute and collaborate to e-learning environments. The influences of social media have reached Arab culture and are quickly spreading. This study highlights the use of these media for self-directed learning (SDL) purposes among medical students. This is a cross-sectional study and the questionnaire was constructed using the Delphi technique at Google (Google Inc., Mountain View, CA, USA) documents and was uploaded to different social media sites. The questionnaire comprised 28 questions, which included information relating to demographic features and utilization of social media during SDL time. The data were entered into Statistical Product and Service Solutions (SPSS) version 21 (IBM Corporation, Armonk, NY, USA) and Pearson chi-squared tests were applied for comparison. We received a total of 103 responses in 1 week, 52 of which (50.5%) were from men. The greatest proportion of responses came from students in their fifth year (35%), followed by those in their fourth year and first year (18.4%). Most students (63%) scored a grade-point average of 4–5 points. Out of the total, only eight students (7.8%) responded that they do not use social network sites at all. Almost one-third of responders (33%) utilized social networks for SDL for 2–3 hours daily, and 84 responders (81%) declared that these social media sites are helpful during preparation for their examinations. Age, sex and academic year have a significant association ( P <0.05) with the use of social media. In conclusion, it is reported that the culture of using of social media is increasing in Arab society; however, we need to provide the guidance for its proper utilization for SDL purposes.

Effect of Social Media Discussion Forums on Learning Outcomes in an Online Course

In this paper we describe how we used Facebook as a complementary tool to our LMS. We collected data on student usage and surveyed student opinion in several online/blended sections. Our hypothesis is that our empirical analysis will find a positive correlation between student usage of Facebook in the online/blended classroom and student learning outcomes.

Social media discussion forums and product innovation - The way forward?

The purpose of this paper is to examine the potential use of social media discussion forums in product innovation. The literature shows the value of sport addicts and hobbyists as innovators in product innovation; hence this study is related to sports. This is an empirical study based on substantial data collected from 28 discussion forums. Altogether 2,178 discussions related to heart rate monitors have been evaluated for this paper.&#x0D; &#x0D; Discussion forums can be regarded as a source of product innovation. However, due to the excessive amount of information in these forums, a planned approach in order to utilize these remarks is necessary. Sport addicts and hobbyists are very interested in product improvements and usage possibilities, forming a considerable resource. Social media discussion forums can replace focus groups, online surveys and panels, and it is easy to reach large groups, test ideas and secure feedback. However, the rapid speed in conversations and excessive need for interaction between individuals set high demands for organizations, as they should clearly decide how to participate, when and how to direct discussions, and how to effectively be present.