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Emojis are digital pictographs used to express ideas and emotions. There are thousands of emojis, some depicting faces with expressions and others depicting objects, animals, and activities. We examined how emoji use on Twitter was related to users’ language use and Big Five personality traits. In the present research, we examined emoji use in tweets for seventy-six twitter accounts belonging to undergraduate students (34 women, 22 men) who also completed an online survey in which they reported personal characteristics including personality traits. With their consent, we retrieved tweets from accounts using the Twitter API and python script. We also analyzed word usage in tweets using the Linguistic Inquiry Word Count (LIWC). The results showed that frequent use of emojis was related to lower levels of openness, but not other Big Five traits. More frequent use of emojis was related to more frequent use of word related to: tone, positive emotion, sad, affect, feel, you pronouns, family, and the body. More frequent use of emojis was related to less frequent use of articles and words related to insight, money, risk, anger, sexual, ingest, informal, and swear words. 

Prior research has demonstrated relationships between personality traits of social media users and the language used in their posts. Few studies have examined whether there are relationships between personality traits of users and how they use emojis in their social media posts. Emojis are digital pictographs used to express ideas and emotions. There are thousands of emojis, which depict faces with expressions, objects, animals, and activities. We conducted a study with two samples (n = 76 andn = 245) in which we examined how emoji use on X (formerly Twitter) related to users’ personality traits and language use in posts. Personality traits were assessed from participants in an online survey. With participants’ consent, we analyzed word usage in posts. Word frequencies were calculated using the Linguistic Inquiry Word Count (LIWC). In both samples, the results showed that those who used the most emojis had the lowest levels of openness to experience. Emoji use was unrelated to the other personality traits. In sample 1, emoji use was also related to use of words related to family, positive emotion, and sadness and less frequent use of articles and words related to insight. In sample 2, more frequent use of emojis in posts was related to more frequent use ofyoupronouns,Ipronouns, and more frequent use of negative function words and words related to time. The results support the view that social media users’ characteristics may be gleaned from the content of their social media posts. 

This paper focuses on the design of a mixed reality-based (MR) simulation environment to train health care personnel in reverse total shoulder arthroplasty (RTSA) procedure. Information-centric models involving interaction with orthopedic surgeons were created as part of a participatory design approach. These information models provided a structural foundation for the design and development of the environments. This paper concludes with a discussion of the preliminary assessment activities which includes studying the impact of such a MR approach on understanding and knowledge acquisition of the targeted surgical procedure. 

This article provides a systematic review of research related to Human–Computer Interaction techniques supporting training and learning in various domains including medicine, healthcare, and engineering. The focus is on HCI techniques involving Extended Reality (XR) technology which encompasses Virtual Reality, Augmented Reality, and Mixed Reality. HCI-based research is assuming more importance with the rapid adoption of XR tools and techniques in various training and learning contexts including education. There are many challenges in the adoption of HCI approaches, which results in a need to have a comprehensive and systematic review of such HCI methods in various domains. This article addresses this need by providing a systematic literature review of a cross-s Q1 ection of HCI approaches involving proposed so far. The PRISMA-guided search strategy identified 1156 articles for abstract review. Irrelevant abstracts were discarded. The whole body of each article was reviewed for the remaining articles, and those that were not linked to the scope of our specific issue were also eliminated. Following the application of inclusion/exclusion criteria, 69 publications were chosen for review. This article has been divided into the following sections: Introduction; Research methodology; Literature review; Threats of validity; Future research and Conclusion. Detailed classifications (pertaining to HCI criteria and concepts, such as affordance; training, and learning techniques) have also been included based on different parameters based on the analysis of research techniques adopted by various investigators. The article concludes with a discussion of the key challenges for this HCI area along with future research directions. A review of the research outcomes from these publications underscores the potential for greater success when such HCI-based approaches are adopted during such 3D-based training interactions. Such a higher degree of success may be due to the emphasis on the design of userfriendly (and user-centric) training environments, interactions, and processes that positively impact the cognitive abilities of users and their respective learning/training experiences. We discovered data validating XR-HCI as an ascending method that brings a new paradigm by enhancing skills and safety while reducing costs and learning time through replies to three exploratory study questions. We believe that the findings of this study will aid academics in developing new research avenues that will assist XR-HCI applications to mature and become more widely adopted.