As social media becomes increasingly ubiquitous, many events are recorded and released on social media platforms, including chemical weapon attacks. We develop an objective tool in order to evaluate brief and unstructured social media videos for analysing sarin exposure from a civilian medical pathology perspective. We developed and validated this new questionnaire using a standardized procedure that includes content domain specification, item pool generation, content validity evaluation, a pilot study, and assessment of reliability and validity. In total, 51 sarin attacks and 48 matched videos were analysed. Cronbach's a for all 20 items was 0.75, which indicates adequate internal reliability. The test-retest reliability was 0.96, which indicates good internal reliability. The inter-observer intraclass correlation coefficient was 0.97. After verifying sampling adequacy with the Kaiser-Meyer-Olkin measure and the factorability of the items with Barlett's test of sphericity, a factor analysis was performed. According to the principal axis factoring, a six-factor solution explained 51.86% of the total variance. The receiver-operating characteristic curve analysis showed that the Video Score Questionnaire has a sensitivity of 0.817, a specificity of 0.478, and an efficiency of 65.3. Therefore, the Video Score Questionnaire is reliable and valid for evaluating sarin attacks from brief and unstructured social media videos. KEY POINTS Chemical weapons are still used as a method of warfare. Social media videos are an important source of information. We developed a validated scale which can analyse sarin exposure in short and unstructured videos.

Visual attention is an essential social element in face-to-face conversations between people. The Army is now using virtual environments with virtual human role-players to provide for the development and practice of leader counseling skills. While literature indicates that virtual humans positively impact learning outcomes, this research contributes to the understanding of how people interact with virtual humans. Specifically, the research investigates a person’s social behavior toward a virtual human in a simulated counseling session. Utilizing a computer-based training environment, this research tracked visual attention toward and acceptance of a virtual human role-player by 120 military counselors. Behavior moderators included attentional influences on the counselor from the level of expression and full-body or close-up views of the virtual human. Results indicate trainees do practice appropriate social attention when the virtual human is speaking. Results also indicate counselors attended to an active more than a static full-body view indicating there is value in nonverbal communication channels. Switching from a full-body to a close-up view did not result in significant changes of the counselor’s visual attention. Further, the research indicates switching views may undermine the perception of a natural interaction. Counselors considered the experience useful. The research suggests study and design considerations to enhance future social skills training environments.

As technology advances, people increasingly converse with computer conversational agents serving in a personal assistant role such as Siri or Cortona. Beyond the personal assistant role, a virtual humans may substitute for a person in another role during a social encounter in a simulated environment. From an experiential or pedantic training perspective, the resulting simulated social encounter may provide a forum by which real people may gain social skills. This article reviews advances in technology and science of virtual humans in faceto-face social encounters with people. An assessment framework is proposed based on a modification of the Schroeder, Adesope, & Gilbert framework [1]. Conversational attributes include verbal content and expression and nonverbal behavior such as head position or inclination, micro and macro facial or body emotional expression, eye gaze and direction, and other facial and other bodily gestures. Using that framework, ten instantiations of virtual humans are analyzed with respect to simulating a person in a bi-directional conversation. Findings and discussion address the question: can a virtual human truly be a social partner with a person for the purpose of social skills training? Within a social skills learning setting, analysis raises concern about the impact of textual data concurrently displayed with verbal message content and expression, and nonverbal behavior. Suggested future advanced technology research includes virtual human eye tracking technology in order to a better understand the cognitive science and behavioral responses associated with periods of engagement and boredom during interactions with a person.