The roles of emojis in mobile phone notifications

The texts in mobile messages are not always easy to decipher since tone and body language is removed from the context. Emojis offer an attractive way to express emotions to avoid misunderstandings of message tone. In this paper we shed the light on the roles of Emojis in phone notification, we conducted an in-situ study to gather phone notification data. We outline the relationship between Emojis and various social network applications including WhatsApp, Facebook and Twitter. Early results allow us to draw several conclusions in relation to number, position, type and sentimental value of Emojis. It turns out that most popular Emojis in one social app is not as popular in the others. Emojis sentimental polarity in Twitter is high and overall number of Emojis is less than Facebook. The sentimental value of Emojis is more meaningful when there are multiple Emoji in one notification

NotiMind: responses to smartphone notifications as affective sensors

Today's mobile phone users are faced with large numbers of notifications on social media, ranging from new followers on Twitter and emails to messages received from WhatsApp and Facebook. These digital alerts continuously disrupt activities through instant calls for attention. This paper examines closely the way everyday users interact with notifications and their impact on users’ emotion. Fifty users were recruited to download our application NotiMind and use it over a five-week period. Users’ phones collected thousands of social and system notifications along with affect data collected via self-reported PANAS tests three times a day. Results showed a noticeable correlation between positive affective measures and keyboard activities. When large numbers of Post and Remove notifications occur, a corresponding increase in negative affective measures is detected. Our predictive model has achieved a good accuracy level using three different classifiers "in the wild" (F-measure 74-78% within-subject model, 72-76% global model). Our findings show that it is possible to automatically predict when people are experiencing positive, neutral or negative affective states based on interactions with notifications. We also show how our findings open the door to a wide range of applications in relation to emotion awareness on social and mobile communication

Spice up Your Chat: The Intentions and Sentiment Effects of Using Emoji

Emojis, as a new way of conveying nonverbal cues, are widely adopted in computer-mediated communications. In this paper, first from a message sender perspective, we focus on people's motives in using four types of emojis -- positive, neutral, negative, and non-facial. We compare the willingness levels of using these emoji types for seven typical intentions that people usually apply nonverbal cues for in communication. The results of extensive statistical hypothesis tests not only report the popularities of the intentions, but also uncover the subtle differences between emoji types in terms of intended uses. Second, from a perspective of message recipients, we further study the sentiment effects of emojis, as well as their duplications, on verbal messages. Different from previous studies in emoji sentiment, we study the sentiments of emojis and their contexts as a whole. The experiment results indicate that the powers of conveying sentiment are different between four emoji types, and the sentiment effects of emojis vary in the contexts of different valences.Comment: 10 pages, published at ICWSM'1

A mood tracking interface for mobile application -to help assess well being in students.

Many students struggle with mental health issues, however, research show that few of them seek help for their problems (Knapstad et al., 2018). In this study, a mobile mood tracking interface is developed with the objective to explore how to best motivate students to track their mood. What the state-of-the-art says about using a mobile application to help students with mental health problems (RQ1) was investigated through a literature review. Research through design (RtD) formed the basis of this research, where a mobile mood tracking interface was developed using an user-centered design process. The interface was evaluated by mental health experts, heuristically by usability experts, and through user testing: design exercise, usability testing, and interviews with students. The design process explored how students perceived the interface (RQ2), and which recommendations designers of a mobile mood tracking interface should consider, in order to best support an intuitive design to motivate students to track their mood (RQ4). In addition, a survey was performed to explore students attitudes towards sharing mental health data (RQ3). The literature review showed that a mobile app that provide self-report could be a good tool to asses well being in students, however, current apps have low engagement within the users. Findings in the prototype, revealed that the way of tracking mood worked fine, however, the students interpreted colors and emojis differently, enjoyed different layouts, and had different notifications preferences. This shows a need for personalization. Students should be able to personalize layout, change notification frequency, and customize colors and emojis on a set of predefined emotion labels. The survey result indicates that students are positive towards sharing mood statistics and notes, however, they are concerned with security and privacy, and thus are less willing to share sensitive data. This thesis contributes to the research field with an analysis of functionality in mental health apps, by producing an artifact, and providing a set of recommendations of what to consider when designing a mood tracking interface for students. Future work can extend these recommendations by performing a longitudinal study investigating motivation, and the interface should be tested with real users, targeting persons with psychological issues.Masteroppgave i informasjonsvitenskapINFO390MASV-INFOMASV-IK

Undergraduates' interpretation on WhatsApp smiley emoji

Undergraduate students, who are digital native, are keen on using emoji (smileys and ideograms) frequently to express themselves emotionally in their digital communication such as WhatsApp Messenger. Nevertheless, sometimes, they got into misunderstanding due to the different emoji's interpretation between the sender and the recipient. Research investigating emoji is still relatively new and this study discusses the diverse interpretations of WhatsApp emoji specifically the smileys among Malaysian undergraduates in a public university. This study attempted to investigate 210 undergraduates' interpretations of 75 smiley (face-like) meanings in WhatsApp Messenger. The respondents were asked to give feedback in self-administrated survey questionnaire to gather information on their interpretation of the smileys used in WhatsApp. A descriptive analysis was conducted on the students' interpretations and the findings disclosed that although the students interpreted a few smileys correctly, they did not know the intended meaning of most of the smileys correctly. The results of this study suggested that the students should know the meaning of the smiley/ emoji used in their digital conversation to able to understand its intended use and to avoid miscommunication in their digital communication. For WhatsApp users, the findings will be beneficial to emphasize the need to understand the emoji's intended meaning for future tolerant and wiser use

OPICO: A platform for collecting and analyzing emoji usage

Emojis have emerged as a popular form of digital communication that can quickly convey big ideas or expressions with a single character. Since their creation in 1999, emojis have become a mainstay in the digital lexicography of instant messaging and social media. However, emojis are traditionally used in conjunction with text, as supplemental metadata. This paper explores the feasibility of emoji-only communication and emoji grammars. To gather emoji-only data, we built Opico, an emoji-first, social media mobile app that allows users to share emoji reactions about the places they visit with their friends. Each post in the app is a one-to-five emoji sentence to express an emotion, sentiment, or description about a location. After collecting over 3500 emoji reactions and having over 900 users on the app, the results demonstrate emoji-only communication provided concise forms of expression about various locations across the world. Data analysis has uncovered the various patterns and linguistics of how users construct emoji-only sentences, building the foundation for an emoji grammar

Reflexive Skills in Teacher Education: A Tweet a Week

Social media has been broadly used in the context of higher education for educational purposes due to students’ familiarity with this type of communication. As one of the most interesting cases, Twitter has often been used in teacher education for many purposes. One of the most unexplored themes is using Twitter for reflexive aims, in which discussions featuring ambiguous and contradictory results about whether the characteristics of such a short format can promote reflexive writing. This study is aimed at contributing to this research gap and explores the possibilities of using Twitter for reflective aims in teacher education, considering the reflective level of students’ tweets and students’ perceptions after engaging on Twitter. For the evaluation of this reflection, a content analysis of tweets texts and emojis has been carried out by coding their content and developing an instrument to assess their reflective level. Additionally, perceptions of students have been collected through an online survey. This study is embedded in a design-based research process that is already in its fourth cycle. Findings show that most tweets are descriptive or analytical, and that tweets are mainly text-based. Furthermore, the data show that low-level reflective tweets may include emojis, which are mainly positive and located at the end of a tweet. The conclusions suggest that Twitter could be more useful when reflections are made during learning rather than on learning.his research and the APC were funded by the Spanish Ministry of Science and Innovation, grant number EDU2017-84223-

MensSana: Design of a mental well-being self-report interface for shop floor workers

A ascensão da Indústria 4.0 trouxe consigo novas tecnologias e oportunidades que estão a mudar a natureza do trabalho, especialmente em ambientes de chão de fábrica. No entanto, essas mudanças também trouxeram novos desafios para os trabalhadores, incluindo desafios na sua saúde mental. Estes trabalhadores, em particular, enfrentam no seu trabalho estressores físicos e mentais que podem afetar seu bem-estar geral, apesar dos esforços da Indústria 4.0. O conceito de Operador 4.0 na Indústria 4.0 introduz muitos operadores, como o Operador Saudável, que enfatiza a centralidade no ser humano e visa melhorar a eficiência e o bem-estar do trabalhador por meio de tecnologias avançadas e análise de dados. Esta tese propõe o desenvolvimento de uma ferramenta protótipo, co-criada e validada no contexto da Indústria 4.0 para medir métricas do trabalhador e do local de trabalho, criando uma imagem holística do trabalhador, sua competência e bem-estar, alinhado ao conceito de um trabalhador "mais saudável" de Romero et al. Essas informações são devolvidas ao trabalhador e apresentadas de maneira legível e compreensível para identificar tendências e informar decisões futuras relacionadas ao trabalho e bem-estar.The rise of Industry 4.0 has brought about new technologies and opportunities that are changing the nature of work, particularly in factory floor settings. However, these changes have also brought about new challenges for workers, including mental health issues. Shop floor workers, in particular, face physical and mental stressors in their work that can impact their overall well-being, despite Industry 4.0 efforts. The Operator 4.0 concept in Industry 4.0 introduces a lot of operators like the Healthy Operator that emphasises human-centricity and aims to improve worker efficiency and well-being through advanced technologies and data analytics. This thesis proposes the development of a prototype tool co-created and validated in the context of Industry 4.0 to measure metrics from the worker and the workplace, creating a holistic picture of the worker, their competence and well-being in line with Romero's et al. concept of a "healthier" worker. This information is returned to the worker and presented in a readable and understandable manner to identify trends and inform future decisions concerning their work and well-being

Understanding subject-based Emoji usage using network science

This is the author accepted manuscript. The final version is available from Springer Nature via the DOI in this recordThe use of “Emoticons” and “Emojis” in social media as well as most online writing has become the de-facto standard on how to express emotions, feelings, etc. Although there are more that 1,000 emojis, not much has been done to understand the way in which people use these characters. The large set of emojis available brings two questions: (i) How can users make full use of the emojis available? and (ii) Would it be possible to build a recommendation system for emoji usage in text? This paper moves towards a greater understanding of emoji usage by mapping possible relations between these special characters in common text. We look at possible regularities in emoji usages in written, subject-specific, text corpora. We build co-occurrence networks of emoji based on two datasets and show that the structure of these networks are not random and more like a truncated power-law, but more interesting, we show that the structure has similar characteristics despite the text being subject-specific

Exploring the attitudes and behaviour of generation Z students towards branded mobile applications.

Master of Commerce. University of KwaZulu-Natal, Pietermaritzburg, 2017.With the increasing mobile activity of the Generation Z market (those born after 1994) in South Africa, marketers’ interest in this social group is rising. This research attempts to uncover the relatively unknown attitudes and behaviour of the youth market in South Africa around branded mobile applications. The research problem focuses on the academic literature gap of the latest group of consumers: Generation Z. Previous studies on mobile marketing have focused on Generation X and Generation Y. Furthermore, only quantitative studies have been performed on the youth market and mobile applications in South Africa. This study is based on the theoretical framework of the Unified Theory of Acceptance and Use of Technology Model 2. The study employed a qualitative framework with focus groups as the data collection method. The focus groups were stratified on gender and the participants ranged from 18-21 years old. The study was conducted at a private tertiary institution in Durban, South Africa. The findings indicate that the participants had both positive and negative attitudes towards branded mobile applications, however there were more positive than negative attitudes. In terms of behaviour, on average, participants had between 7-10 apps on their phone but only used 4-6 apps every day. The findings revealed the most popular branded mobile application as Whatsapp. Furthermore, social influences, facilitating conditions, performance expectancy, effort expectancy, hedonic motivation, price value and habit are all influencers of branded mobile application behaviour. The results identify age, gender and experience as moderating factors related to the attitudes and behaviour of Generation Z students with mobile apps. As a recommendation, the issue of privacy and its effect on mobile app adoption is a factor to be researched in the future for academics. The research also provides recommendations for marketers and app developers such as incorporating permission marketing into mobile applications