Mengdi Li, Eugene Chng, Alain Yee Loong Chong and Simon See
Emoji has become an essential component of any digital communication and its importance can be attested to by its sustained popularity and widespread use. However, research in…
Abstract
Purpose
Emoji has become an essential component of any digital communication and its importance can be attested to by its sustained popularity and widespread use. However, research in Emojis is rarely to be seen due to the lack of data at a greater scale. The purpose of this paper is to systematically analyse and compare the usage of Emojis in a cross-cultural manner.
Design/methodology/approach
This research conducted an empirical analysis using a large-scale, cross-regional emoji usage data set from Twitter, a platform where the limited 140 characters allowance has made it essential for the inclusion of emojis within tweets. The extremely large textual data set covers a period of only two months, but the 673m tweets authored by more than 2,081,542 unique users is a sufficiently large sample for the authors to yield significant results.
Findings
This research discovered that the categories and frequencies of Emojis communicated by users can provide a rich source of data to understand cultural differences between Twitter users from a large range of demographics. This research subsequently demonstrated the preferential use of Emojis complies with Hofstede’s Cultural Dimensions Model, in which different representations of demographics and culture within countries present significantly different use of Emojis to communicate emotions.
Originality/value
This study provides a robust example of how to strategically conduct research using large-scale emoji data to pursue research questions previously difficult. To the best of authors’ knowledge, the present study pioneers the first systematic analysis and comparison of the usage of emojis on Twitter across different cultures; it is the largest, in terms of the scale study of emoji usage to-date.
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The need to digitise is an awareness that is shared across our community globally, and yet the probability of the intersection between resources, expertise and institutions are…
Abstract
Purpose
The need to digitise is an awareness that is shared across our community globally, and yet the probability of the intersection between resources, expertise and institutions are not as prospective. A strategic view towards the long-term goal of cultivating and digitally upskilling the younger generation, building a community and creating awareness with digital activities that can be beneficial for cultural heritage is necessary.
Design/methodology/approach
The work involves distributing tasks between stakeholders and local volunteers. It uses close-range photogrammetry for reconstructing the entire heritage site in 3D, and outlines achievable digitisation activities in the crowdsourced, close-range photogrammetry of a 19th century Cheah Kongsi clan temple located in George Town, a UNESCO World Heritage Site in Penang, Malaysia.
Findings
The research explores whether loosely distributing photogrammetry work that partially simulates an unorganised crowdsourcing activity can generate complete models of a site that meets the criteria set by the needs of the clan temple. The data acquired were able to provide a complete visual record of the site, but the 3D models that was generated through the distributed task revealed gaps that needed further measurements.
Practical implications
Key lessons learned in this activity is transferable. Furthermore, the involvement of volunteers can also raise awareness of ownership, identity and care for local cultural heritage.
Social implications
Key lessons learned in this activity is transferable. Furthermore, the involvement of volunteers can also raise awareness of identity, ownership, cultural understanding, and care for local cultural heritage.
Originality/value
The value of semi-formal activities indicated that set goals can be achieved through crowdsourcing and that the new generation can be taught both to care for their heritage, and that the transfer of digital skills is made possible through such activities. The mass crowdsourcing activity is the first of its kind that attempts to completely digitise a cultural heritage site in 3D via distributed activities.
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Hong-liang Sun, Eugene Ch’ng and Simon See
The purpose of this paper is to investigate political influential spreaders in Twitter at the juncture before and after the Malaysian General Election in 2013 (MGE2013) for the…
Abstract
Purpose
The purpose of this paper is to investigate political influential spreaders in Twitter at the juncture before and after the Malaysian General Election in 2013 (MGE2013) for the purpose of understanding if the political sphere within Twitter reflects the intentions, popularity and influence of political figures in the year in which Malaysia has its first “social media election.”
Design/methodology/approach
A Big Data approach was used for acquiring a series of longitudinal data sets during the election period. The work differs from existing methods focusing on the general statistics of the number of followers, supporters, sentiment analysis, etc. A retweeting network has been extracted from tweets and retweets and has been mapped to a novel information flow and propagation network we developed. The authors conducted quantitative studies using k-shell decomposition, which enables the construction of a quantitative Twitter political propagation sphere where members posited at the core areas are more influential than those in the outer circles and periphery.
Findings
The authors conducted a comparative study of the influential members of Twitter political propagation sphere on the election day and the day after. The authors found that representatives of political parties which are located at the center of the propagation network are winners of the presidential election. This may indicate that influential power within Twitter is positively related to the final election results, at least in MGE2013. Furthermore, a number of non-politicians located at the center of the propagation network also significantly influenced the election.
Research limitations/implications
This research is based on a large electoral campaign in a specific election period, and within a predefined nation. While the result is significant and meaningful, more case studies are needed for generalized application for identifying potential winning candidates in future social-media fueled political elections.
Practical implications
The authors presented a simple yet effective model for identifying influential spreaders in the Twitter political sphere. The application of the authors’ approach yielded the conclusion that online “coreness” score has significant influence to the final offline electoral results. This presents great opportunities for applying the novel methodology in the upcoming Malaysian General Election in 2018. The discovery presented here can be used for understanding how different players of political parties engage themselves in the election game in Twitter. The approach can also be adopted as a factor of influence for offline electoral activities. The conception of a quantitative approach in electoral results greatly influenced by social media means that comparative studies could be made in future elections.
Originality/value
Existing works related to general elections of various nations have either bypassed or ignored the subtle links between online and offline influential propagations. The modeling of influence from social media using a longitudinal and multilayered approach is also rarely studied. This simple yet effective method provides a new perspective of practice for understanding how different players behave and mutually shape each other over time in the election game.
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Mengdi Li, Eugene Ch’ng, Alain Yee Loong Chong and Simon See
Recently, various Twitter Sentiment Analysis (TSA) techniques have been developed, but little has paid attention to the microblogging feature – emojis, and few works have been…
Abstract
Purpose
Recently, various Twitter Sentiment Analysis (TSA) techniques have been developed, but little has paid attention to the microblogging feature – emojis, and few works have been conducted on the multi-class sentiment analysis of tweets. The purpose of this paper is to consider the popularity of emojis on Twitter and investigate the feasibility of an emoji training heuristic for multi-class sentiment classification of tweets. Tweets from the “2016 Orlando nightclub shooting” were used as a source of study. Besides, this study also aims to demonstrate how mapping can contribute to interpreting sentiments.
Design/methodology/approach
The authors presented a methodological framework to collect, pre-process, analyse and map public Twitter postings related to the shooting. The authors designed and implemented an emoji training heuristic, which automatically prepares the training data set, a feature needed in Big Data research. The authors improved upon the previous framework by advancing the pre-processing techniques, enhancing feature engineering and optimising the classification models. The authors constructed the sentiment model with a logistic regression classifier and selected features. Finally, the authors presented how to visualise citizen sentiments on maps dynamically using Mapbox.
Findings
The sentiment model constructed with the automatically annotated training sets using an emoji approach and selected features performs well in classifying tweets into five different sentiment classes, with a macro-averaged F-measure of 0.635, a macro-averaged accuracy of 0.689 and the MAEM of 0.530. Compared to those experimental results in related works, the results are satisfactory, indicating the model is effective and the proposed emoji training heuristic is useful and feasible in multi-class TSA. The maps authors created, provide a much easier-to-understand visual representation of the data, and make it more efficient to monitor citizen sentiments and distributions.
Originality/value
This work appears to be the first to conduct multi-class sentiment classification on Twitter with automatic annotation of training sets using emojis. Little attention has been paid to applying TSA to monitor the public’s attitudes towards terror attacks and country’s gun policies, the authors consider this work to be a pioneering work. Besides, the authors have introduced a new data set of 2016 Orlando Shooting tweets, which will be made available for other researchers to mine the public’s political opinions about gun policies.
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Eugene Ch’ng, Shengdan Cai, Tong Evelyn Zhang and Fui-Theng Leow
The purpose of this paper is to present the rationale for democratising the digital reproduction of cultural heritage via “mass photogrammetry”, by providing approaches to…
Abstract
Purpose
The purpose of this paper is to present the rationale for democratising the digital reproduction of cultural heritage via “mass photogrammetry”, by providing approaches to digitise objects from cultural heritage collections housed in museums or private spaces using devices and photogrammetry techniques accessible to the public. The paper is intended as a democratised approach rather than as a “scientific approach” for the purpose that mass photogrammetry can be achieved at scale.
Design/methodology/approach
The methodology aims to convert the art of photogrammetry into a more mechanical approach by overcoming common difficulties faced within exhibition spaces. This approach is replicable and allows anyone possessing inexpensive equipment with basic knowledge of photogrammetry to achieve acceptable results.
Findings
The authors present the experience of acquiring over 300 3D models through photogrammetry from over 25 priority sites and museums in East Asia. The approach covers the entire process from capturing to editing, and importing 3D models into integrated development environments for displays such as interactive 3D, Virtual Reality and Augmented Reality.
Practical implications
The simplistic approach for democratised, mass photogrammetry has implications for stirring public interests in the digital preservation of heritage objects in countries where museums and cultural institutions have little access to digital teams, provided that Intellectual Property issues are cared for. The approach to mass photogrammetry also means that personal cultural heritage objects hidden within the homes of various societies and relics in circulation in the antiques market can be made accessible globally at scale.
Originality/value
This paper focuses on the complete practical nature of photogrammetry conducted within cultural institutions. The authors provide a means for the public to conduct good photogrammetry so that all cultural heritage objects can be digitally recorded and shared globally so as to promote the cross-cultural appreciation of material cultures from the past.
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The purpose of this paper is to present a Big Data solution as a methodological approach to the automated collection, cleaning, collation, and mapping of multimodal, longitudinal…
Abstract
Purpose
The purpose of this paper is to present a Big Data solution as a methodological approach to the automated collection, cleaning, collation, and mapping of multimodal, longitudinal data sets from social media. The paper constructs social information landscapes (SIL).
Design/methodology/approach
The research presented here adopts a Big Data methodological approach for mapping user-generated contents in social media. The methodology and algorithms presented are generic, and can be applied to diverse types of social media or user-generated contents involving user interactions, such as within blogs, comments in product pages, and other forms of media, so long as a formal data structure proposed here can be constructed.
Findings
The limited presentation of the sequential nature of content listings within social media and Web 2.0 pages, as viewed on web browsers or on mobile devices, do not necessarily reveal nor make obvious an unknown nature of the medium; that every participant, from content producers, to consumers, to followers and subscribers, including the contents they produce or subscribed to, are intrinsically connected in a hidden but massive network. Such networks when mapped, could be quantitatively analysed using social network analysis (e.g. centralities), and the semantics and sentiments could equally reveal valuable information with appropriate analytics. Yet that which is difficult is the traditional approach of collecting, cleaning, collating, and mapping such data sets into a sufficiently large sample of data that could yield important insights into the community structure and the directional, and polarity of interaction on diverse topics. This research solves this particular strand of problem.
Research limitations/implications
The automated mapping of extremely large networks involving hundreds of thousands to millions of nodes, encapsulating high resolution and contextual information, over a long period of time could possibly assist in the proving or even disproving of theories. The goal of this paper is to demonstrate the feasibility of using automated approaches for acquiring massive, connected data sets for academic inquiry in the social sciences.
Practical implications
The methods presented in this paper, together with the Big Data architecture can assist individuals and institutions with a limited budget, with practical approaches in constructing SIL. The software-hardware integrated architecture uses open source software, furthermore, the SIL mapping algorithms are easy to implement.
Originality/value
The majority of research in the literature uses traditional approaches for collecting social networks data. Traditional approaches can be slow and tedious; they do not yield adequate sample size to be of significant value for research. Whilst traditional approaches collect only a small percentage of data, the original methods presented here are able to collect and collate entire data sets in social media due to the automated and scalable mapping techniques.
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Augustine Pang, Ratna Damayanti and Eugene Yong-Sheng Woon
In 2015, Malaysia’s investment vehicle, 1Malaysia Development Berhad (1MDB), came under international scrutiny after it amassed a debt of US$11 billion (10.3 billion) (Wright &…
Abstract
In 2015, Malaysia’s investment vehicle, 1Malaysia Development Berhad (1MDB), came under international scrutiny after it amassed a debt of US$11 billion (10.3 billion) (Wright & Clark, 2015), which it had difficulty repaying. More disturbingly, investigators found that US$700 million (658 million) was transferred into the personal bank account of Malaysia’s prime minister, Najib Razak, founder and chairman of 1MDB’s advisory board (Wright & Clark, 2015). Najib was also accused of embezzling state money (Reuters, 2015) and damaging the image of the country (“Najib tried to bribe me”, 2015). This chapter aims to examine the strategies used by the Malaysian prime minister to repair his image in the 1MDB scandal, the effectiveness of these strategies, and how these impacted Malaysia’s public diplomacy efforts in restoring the country’s image and reputation. Findings showed that the prime minister denied wrongdoing, and simultaneously bolstered his position and promised to turn 1MDB around. In contrast to the current explication of Benoit and Pang’s (2008) image repair strategies, Najib’s way of attacking the accusers sheds light into how image repair strategies may be operationalized in the Asian context. A new image repair strategy – diversion – is proposed to be added to the existing framework.
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Purpose – This study examines the relationship between endorsement of positive stereotypes of women and support for women's rights to shed light on the role that endorsement of…
Abstract
Purpose – This study examines the relationship between endorsement of positive stereotypes of women and support for women's rights to shed light on the role that endorsement of positive stereotypes may play in maintaining social stratification.
Design/methodology/approach – The study uses data collected from a web-based survey of 181 male undergraduate students in six different universities and colleges to examine the relationship between the endorsement of positive stereotypes of women and support for women's rights. The paper examines four ordinary least squares (OLS) regression models to determine the relationship and utilizes the statistical software Stata 9.2.
Findings – Rather than a simple direct relationship, the findings suggest that the relationship between the endorsement of positive stereotypes and support for women's rights varies based on the level of hostile sexism. Increased endorsement of positive stereotypes of women was associated with decreased support for women's rights among males with the lowest level of hostile sexism, but the opposite relationship was found for males at the mean and the highest level of hostile sexism.
Research limitations/implications – The findings suggest that endorsement of positive stereotypes plays a unique role for males who do not endorse traditional sexist attitudes. Although data are not available to clarify what processes might be undergirding the relationship, the author suggests directions for future research.
Practical implications – Given the relationship found, prejudice reduction interventions that rely on the promotion of positive stereotypes of various social groups should be closely examined to determine if they actually foster attitudes that are detrimental for the eradication of social stratification.
Originality/value – This study is one of the first to examine the possible negative impacts of endorsement of positive stereotypes of women on gender stratification through a moderated relationship with levels of hostile sexism.
Ellen Middaugh, Sherry Bell and Mariah Kornbluh
In response to concerns about fake news (Allcott et al., 2019) and polarization (Wollebaek et al., 2019), youth media literacy interventions have emerged to teach strategies for…
Abstract
Purpose
In response to concerns about fake news (Allcott et al., 2019) and polarization (Wollebaek et al., 2019), youth media literacy interventions have emerged to teach strategies for assessing credibility of online news (McGrew et al., 2018) and producing media to mobilize others for civic goals (Kahne et al., 2016). However, in light of evidence that practices learned in classroom contexts do not reliably translate to the context of sharing social media (Middaugh, 2018), this study aims to provide a better understanding of youth social media practices needed to design meaningful and relevant educational experiences.
Design/methodology/approach
Semistructured interviews with a think-aloud component were conducted with a diverse sample of 18 California youth (15–24) to learn about factors that guide behavior as they access, endorse, share, comment and produce civic media.
Findings
Findings suggest a shift toward reliance on incidental exposure and noninstitutional sources when accessing information and a tendency toward endorsement and circulation of posts (vs producing original posts) when engaging with civic issues on social media. As participants engaged in these practices, they not only applied judgments of credibility and civic impact but also concerned for personal relevance, relational considerations and fit with internet culture.
Originality/value
The authors recommend moving beyond models that reflect linear processes of effortful search, credibility analysis and production. Instead, the authors propose a new dynamic model of civic media literacy in which youth apply judgments of credibility, relational considerations, relevance to lived experience, civic impact and fit with internet culture as they receive, endorse, share, comment on and produce media in a nonlinear fashion.
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Gerald F. Davis and J. Adam Cobb
This chapter reviews the origins and primary arguments of resource dependence theory and traces its influence on the subsequent literatures in multiple social science and…
Abstract
This chapter reviews the origins and primary arguments of resource dependence theory and traces its influence on the subsequent literatures in multiple social science and professional disciplines, contrasting it with Emerson's power-dependence theory. Recent years have seen an upsurge in the theory's citations in the literature, which we attribute in part to Stanford's position of power in the network of academic exchange. We conclude with a review of some promising lines of recent research that extend and qualify resource dependence theory's insights, and outline potentially fruitful areas of future research.