Emoticon-based Ambivalent Expression: A Hidden Indicator for Unusual Behaviors in Weibo

Recent decades have witnessed online social media being a big-data window for quantificationally testifying conventional social theories and exploring much detailed human behavioral patterns. In this paper, by tracing the emoticon use in Weibo, a group of hidden "ambivalent users" are disclosed for frequently posting ambivalent tweets containing both positive and negative emotions. Further investigation reveals that this ambivalent expression could be a novel indicator of many unusual social behaviors. For instance, ambivalent users with the female as the majority like to make a sound in midnights or at weekends. They mention their close friends frequently in ambivalent tweets, which attract more replies and thus serve as a more private communication way. Ambivalent users also respond differently to public affairs from others and demonstrate more interests in entertainment and sports events. Moreover, the sentiment shift of words adopted in ambivalent tweets is more evident than usual and exhibits a clear "negative to positive" pattern. The above observations, though being promiscuous seemingly, actually point to the self regulation of negative mood in Weibo, which could find its base from the emotion management theories in sociology but makes an interesting extension to the online environment. Finally, as an interesting corollary, ambivalent users are found connected with compulsive buyers and turn out to be perfect targets for online marketing.Comment: Data sets can be downloaded freely from www.datatang.com/data/47207 or http://pan.baidu.com/s/1mg67cbm. Any issues feel free to contact [email protected]

Relationships between emoticon usage and recipient groups in students’ text messages

Emoticons are pictographic representations of facial expressions that are used to convey emotions in text messages and other similar methods of communication. Most research on emoticons has examined how they are used in public forums rather than in private messaging. Using a sample of undergraduate students (n=106; male 52.83%; mean age 20.26 years, SD 1.93), this study examines the use of emoticons in private text communication. Results reveal that emoticon usage is highest amongst friends, followed by siblings, then parents, other family members and more distant connections. Emoticons representing positive emotions are more commonly used than those representing strong negative emotions. Emoticons representing relief were found to be used particularly within peer group communication, whereas emoticons representing contentment were used more with family members and other, more distant, connections. The use of the “Relieved” emoticon with peers may reflect overcoming the stressors associated with shared educational challenges, whereas using the “Content” emoticon outside peers and family may represent emotional modulation and presentation

Sentiment Analysis and Opinion Mining within Social Networks using Konstanz Information Miner

Evaluations, opinions, and sentiments have become very obvious due to rapid emerging interest in ecommerce which is also a significant source of expression of opinions and analysis of sentiment. In this study, a general introduction on sentiment analysis, steps of sentiment analysis, sentiments analysis applications, sentiment analysis research challenges, techniques used for sentiment analysis, etc., were discussed in detail. With these details given, it is hoped that researchers will engage in opinion mining and sentiment analysis research to attain more successes correlated to these issues. The research is based on data input from web services and social networks, including an application that performs such actions. The main aspects of this study are to statistically test and evaluate the major social network websites: In this case Twitter, because it is has rich data source and easy within social networks tools. In this study, firstly a good understanding of sentiment analysis and opinion mining research based on recent trends in the field is provided. Secondly, various aspects of sentiment analysis are explained. Thirdly, various steps of sentiment analysis are introduced. Fourthly, various sentiment analysis, research challenges are discussed. Finally, various techniques used for sentiment analysis are explained and Konstanz Information Miner (KNIME) that can be used as sentiment analysis tool is introduced. For future work, recent machine learning techniques including big data platforms may be proposed for efficient solutions for opinion mining and sentiment analysi

Use of Drawing as a Communication Tool for alleviating digital anxiety: Exploring digital anxiety in smart mobile users

The ever-present smart mobile device has changed the everyday life of users in both positive and negative ways, and connects users’ lives online and offline. The existence of fewer gaps between online and offline worlds has shaped a new form of social relationship, new ways of thinking, and had sparked changes in smart mobile users’ behaviour. This thesis investigates the problem of digital anxiety among smart mobile users. The aim of this research project is to investigate how digital drawing affects digital anxiety in the smart mobile user. The research is based on the premise that drawing is a communication tool, and it investigates what types of digital drawing content help the smart mobile user relieve their digital anxiety. This research proposes guidelines for the use of drawing to help the smart mobile user who is experiencing digital anxiety. First, I established digital anxiety as a theoretical construct, and then conducted exploratory studies to investigate the practical problems faced by the smart mobile user. I determined the meaning of digital anxiety, and the precise symptoms experienced by the user suffering from digital anxiety, through a theoretical framework and an exploratory study. Lastly, I conducted empirical studies aimed at designing a method of measuring the level of digital anxiety. This method was tested with hundreds of participants, and was used for conducting the digital drawing experiment at the end of my research project. Overall, this thesis establishes the scope for determining digital anxiety, provides a method of quantifying digital anxiety, and demonstrates the use of digital drawing to relieve digital anxiety in the smart mobile user. I conclude that my research investigates the use of drawing as a communication tool for smart mobile users as a way of improving their memory, emotional wellbeing, and social relationships. I hope my research can serve as a guideline or a methodology in the design of an educational programme or high-tech industries on the basis of a cognition-mediated model

Situating Conventions of Health: Transformations, Inaccuracies, and the Limits of Measuring in the Field of Self-Tracking

How is doing health transformed into a measurable entity? Based on empirical research, we will analyze relevant aspects of quantifying health in two distinct fields: diet and mood-tracking. From the perspective of the economics of convention, self-trackers within these fields are investing in new forms and measures of equivalence for how health can be measured and handled. In doing so, they are confronting three main obstacles: the inaccuracy of measuring, the cumbersome materiality of objects and everyday practice, and the fuzzy relation of everyday doings and measuring. On the one hand, self-trackers are striving for practical consent over what an “accurate” measuring looks like and in what cases inaccuracy can respectively not be tolerated. On the other hand, self-trackers draw on varying criteria for adequate accuracy depending on how they practically integrate their tracking practices into everyday life. In the economics of convention, objects are granted a vital role, supporting competent everyday actors in their coordination efforts as well as tackling normative and ethical issues. We suggest that technologies such as sensors, mHealth applications, and smartphones are involved in everyday practices as intermediate objects in varying engagements and negotiation processes. In both fields of self-tracking, quite a unique configuration of measuring, objects, resistiveness, and engagements (Thévenot 2002, 2014) emerges, making present conventions of health evasive and fragmented, and still quite unavailable to health organizations, policy makers, and users alike

A culturicon design model for communication across culture

Emoticons are important in Computer-Mediated Communication due to its capability to express emotions/actions without face-to-face meeting. However, existing emoticons are still incompatible and lack some human expressions that limit user’s selection, particularly in terms of culture. Based on the comprehensive literature review conducted, the study regarding emoticons in cultural perspective is limited and there are demand for more cultural-based emoticons to be developed. To solve the issue, this study developed a model named Culturicon Design Model (CDM) by incorporating appropriate cultural dimensions and icon design principles, where Culturicon is the combination of ‘culture’ and ‘icon’. The components of CDM were determined based on previous study’s findings. CDM was then verified through expert review by applying a convergent parallel mixed method that measured the model’s components, flow, and readability, involving 11 experts. Then, CDM was validated by applying an explanatory sequential mixed method involving two phases – validation by designers and validation by end users. Validation by designers measured the components of the model in terms of gain satisfaction, interface satisfaction, task support satisfaction, and emoticon samples’ development, involving five designers. The validation by the end user was performed through focus group discussions, involving eight participants. Thematic analysis was used to analyse focus group’s results. The final version of CDM comprises five cultural dimensions (high power distance, high collectivism, low uncertainty avoidance, moderate masculinity/femininity, and long-term relationships), and eight Human Computer Interaction (HCI) icon design principles (familiar, understandable, attractive, coherent, informative, distinct, memorable, and legible). Focus group’s result showed that the emoticon’s samples represent the cultural elements, fulfilled the HCI icon design principles, and useful in their communication across culture. CDM contributed to the body of knowledge in HCI. It can be a guideline for designers to develop Culturicon in the future, hence providing more emoticon selections from local culture to satisfy end user’s needs

Emergence of Things Felt: Harnessing the Semantic Space of Facebook Feeling Tags

In 2013 Facebook launched a feature allowing users to add a feeling tag to their posts. We have collected 18 months worth of such public posts. Our aim is to map the semantic space of ‘Facebook feelings’ to understand patterns in how feelings are tagged and how they can be described in terms of valence and arousal. Our findings reveal temporal and social patterns in the most commonly shared feelings. In line with the ‘exhibitional’ nature of Facebook, our analyses indicate that ‘extreme’ feelings, such as excitement and anger, may be expressed in even more extreme levels of both valence and arousal. Facebook also provides novel emotional scripts (e.g., “meh”) that help people express feelings in ways that traditionally socialized feelings do not. This understanding of the semantic space of ‘Facebook feelings’ ultimately serves to inform the development of an automatic ‘Feelings Meter’

Information aggregation and computational intelligence

This study examines the possibility that the computational intelligence (CI) inspired tools can effectively aggregate the rich information generated from the Web 2.0 economy and, thereby, enhance the quality of decision-making. Despite many advancements and commendable applications of CI in recent years, this issue has not been well addressed. We argue that this question is intimately related to the central issue of the socialist calculation debate since the time of Friedrich Hayek. In terms of information aggregation, we examine whether there is a better engineering than the market mechanism. More precisely, we focus on whether the CI-driven sentiment analysis can generate signals like prices and whether CI can process unstructured text data better than the market. We argue that Web 2.0 economy may not be able to set us free from information overload problems that have long coexisted with the presence of markets. We attribute this to the tacitness and subjectivity of knowledge and the recursive (feedback) characteristic of the sentiments. In this sense, Hayek’s fundamental assertion that the effectiveness of the market mechanism may not be so much conditioned on the information and communication technology still applies