scholarly journals Emotional Expression of #body on Instagram

2020 ◽  
Vol 6 (2) ◽  
pp. 205630512092477 ◽  
Author(s):  
Clelia Malighetti ◽  
Simona Sciara ◽  
Alice Chirico ◽  
Giuseppe Riva
Keyword(s):  
Artificial Intelligence ◽  
Body Image ◽  
Emotional Expression ◽  
Image Representation ◽  
Future Research ◽  
Discrete Emotions ◽  
Emotional Model ◽  
Artificial Intelligence Technology ◽  
Program Interface

Our aim was to explore emotions in Instagram images marked with hashtags referring to body image–related components using an artificial intelligence–based discrete emotional analysis. A total of 500 Instagram photos marked by specific hashtags related to body image components were analyzed and specific discrete emotions expressed in each picture were detected using the Emotion application program interface API from Microsoft Azure Cognitive Service. Results showed that happiness and neutrality were the most intense and recognizable emotions expressed in all images. Happiness intensity was significantly higher in images with #bodyimage and #bodyconfidence and higher levels of neutral emotion were found in images tagged with #body, #bodyfitness, and #thininspirational. This study integrated a discrete emotional model with the conventional dimensional one, and offered a higher degree of granularity in the analysis of emotions–body link on Instagram through an artificial intelligence technology. Future research should deepen the use of discrete emotions on Instagram and the role of neutrality in body image representation.

Comment: A role of Language in Infant Emotion Concept Acquisition

2020 ◽  
Vol 12 (4) ◽  
pp. 251-253 ◽  
Author(s):  
Holly Shablack ◽  
Andrea G. Stein ◽  
Kristen A. Lindquist
Keyword(s):  
Concept Learning ◽  
Developmental Trajectory ◽  
Concept Acquisition ◽  
Future Research ◽  
Discrete Emotions ◽  
Emotion Development ◽  
Discrete Emotion ◽  
Development Literature ◽  
Emotion Labels

Ruba and Repacholi (2020) review an important debate in the emotion development literature: whether infants can perceive and understand facial configurations as instances of discrete emotion categories. Consistent with a psychological constructionist account (Lindquist & Gendron, 2013; Shablack & Lindquist, 2019), they conclude that infants can perceive valence on faces, but argue the evidence is far from clear that infants perceive and understand discrete emotions. Ruba and Repacholi outline a novel developmental trajectory of emotion perception and understanding in which early emotion concept learning may be language-independent. In this comment, we argue that language may play a role in emotion concept acquisition even prior to children’s ability to produce emotion labels. We look forward to future research addressing this hypothesis.

Do Emotions Cause Eating? The Role of Previous Experiences and Social Context in Emotional Eating

2019 ◽  
Vol 28 (3) ◽  
pp. 234-240 ◽  
Author(s):  
Gizem Altheimer ◽  
Heather L. Urry
Keyword(s):  
Social Context ◽  
Emotional Eating ◽  
Negative Emotion ◽  
Negative Mood ◽  
Experimental Studies ◽  
Future Research ◽  
Discrete Emotions ◽  
Future Studies ◽  
Desire To Eat

Emotional eating is defined as an increase in eating following negative emotion. Self-reported emotional eating has been associated with physical-health concerns. However, experimental studies indicate that negative-mood inductions do not reliably lead to increased eating in healthy eaters, not even among those with a high desire to eat when emotional. We argue that experimental studies will help us understand emotional eating only if they account for the following ideas: (a) Emotional eating may require that people learn to associate emotion with eating, (b) emotional eating may follow only specific discrete emotions, and (c) emotional eating may depend on social context. Each of these points suggests a fruitful direction for future research. Specifically, future studies must acknowledge, identify, and account for variations in the extent to which people have learned to associate emotions with eating; assess or elicit strong discrete emotions; and systematically examine the effect of social context on emotional eating.

scholarly journals RESEARCH ON THE ROLE OF ARTIFICIAL INTELLIGENCE TECHNOLOGY IN UNIVERSITIES BRAND INTEGRATED MARKETING COMMUNICATION

2021 ◽  
pp. 83-85
Author(s):  
Lingling Wu ◽  
Yury Danko
Keyword(s):  
Artificial Intelligence ◽  
Communication Channels ◽  
Current Situation ◽  
Technical Support ◽  
Marketing Communication ◽  
Integrated Marketing ◽  
Integrated Marketing Communication ◽  
Brand Building ◽  
Artificial Intelligence Technology

With the intensification of competition among universities, brand building has gradually become an important content that universities at home and abroad attach great importance to. In the current situation of declining influence of traditional publicity channels and limited influence of self-built media, artificial intelligence technology can provide all-round technical support for university brand integrated marketing communication in terms of communication content and communication channels.

scholarly journals The Perfect Storm: A Developmental–Sociocultural Framework for the Role of Social Media in Adolescent Girls’ Body Image Concerns and Mental Health

2021 ◽  
Author(s):  
Sophia Choukas-Bradley ◽  
Savannah Roberts ◽  
Anne J. Maheux ◽  
Jacqueline Nesi
Keyword(s):  
Mental Health ◽  
Social Media ◽  
Body Image ◽  
Peer Relationships ◽  
Adolescent Girls ◽  
Physical Appearance ◽  
Future Research ◽  
Body Image Concerns ◽  
Perfect Storm

In this theoretical review paper, we provide a developmental–sociocultural framework for the role of social media (SM) in contributing to adolescent girls’ body image concerns, and in turn, depressive symptoms and disordered eating. We propose that the features of SM (e.g., idealized images of peers, quantifiable feedback) intersect with adolescent developmental factors (e.g., salience of peer relationships) and sociocultural gender socialization processes (e.g., societal over-emphasis on girls’ and women’s physical appearance) to create the “perfect storm” for exacerbating girls’ body image concerns. We argue that, ultimately, body image concerns may be a key mechanism underlying associations between adolescent girls’ SM use and mental health. In the context of proposing this framework, we provide empirical evidence for how SM may increase adolescent girls’ body image concerns through heightening their focus on: (1) other people’s physical appearance (e.g., through exposure to idealized images of peers, celebrities, and SM influencers; quantifiable indicators of approval); and (2) their own appearance (e.g., through appearance-related SM consciousness; exposure to one’s own image; encouraging over-valuing of appearance; and peer approval of photos/videos). Our framework highlights new avenues for future research on adolescent girls’ SM use and mental health, which recognize the central role of body image.

scholarly journals Current and emerging artificial intelligence applications for pediatric musculoskeletal radiology

2021 ◽  
Author(s):  
Amaka C. Offiah
Keyword(s):  
Artificial Intelligence ◽  
Pediatric Radiology ◽  
Bone Age ◽  
Future Research ◽  
Fracture Detection ◽  
Musculoskeletal Radiology ◽  
Age Assessment ◽  
Adult World ◽  
Bone Age Assessment

AbstractArtificial intelligence (AI) is playing an ever-increasing role in radiology (more so in the adult world than in pediatrics), to the extent that there are unfounded fears it will completely take over the role of the radiologist. In relation to musculoskeletal applications of AI in pediatric radiology, we are far from the time when AI will replace radiologists; even for the commonest application (bone age assessment), AI is more often employed in an AI-assist mode rather than an AI-replace or AI-extend mode. AI for bone age assessment has been in clinical use for more than a decade and is the area in which most research has been conducted. Most other potential indications in children (such as appendicular and vertebral fracture detection) remain largely in the research domain. This article reviews the areas in which AI is most prominent in relation to the pediatric musculoskeletal system, briefly summarizing the current literature and highlighting areas for future research. Pediatric radiologists are encouraged to participate as members of the research teams conducting pediatric radiology artificial intelligence research.

SIGNIFICANT ROLE OF AI & ML TECHNIQUES USED IN IMPROVEMENT OF CYBER SECURITY

2021 ◽  
Vol 12 (1) ◽  
pp. 80-89
Author(s):  
Muskan Kumari ◽  
Keyword(s):  
Artificial Intelligence ◽  
Cyber Security ◽  
Cyber Attacks ◽  
Current Status ◽  
Future Research ◽  
Engineering Managers ◽  
Network Protection ◽  
Machine Leaning ◽  
Expert Community

Cyber Security has become an arising challenge for business information system in current era. AI (Artificial Intelligence) is broadly utilized in various field, however it is still generally new in cyber security. Nonetheless, the applications in network protection are significant for everybody`s day by day life. In this paper, we present the current status of AI in cyber security field, and afterward portray a few contextual investigations and uses of AI to help the community including engineering managers, teachers, educators, business people, and understudies to more readily comprehend this field, for example, the difficulties and uncertain issues of AI in online protection. According to the new challenges, the expert community has two main approaches: to adopt the philosophy and methods of Military Intelligence, and to use Artificial Intelligence methods for counteraction of Cyber Attacks. Cyber security is a vital danger for any business as the quantity of attacks is expanding. Developing of attacks on cyber security is undermining our reality. AI (Artificial Intelligence) and ML (Machine Leaning) can help identify dangers and give proposals to cyber Analyst. Advancement of appropriation of AI/ML applied to cyber security requires banding together of industry, the scholarly community, and government on a worldwide scale. We also discuss future research opportunities associated with the development of AI techniques in the cyber security ?eld across a scope of utilization areas.

Artificial intelligence technology applications in the pathologic diagnosis of the gastrointestinal tract

2020 ◽  
Vol 16 (34) ◽  
pp. 2845-2851
Author(s):  
Leonardo S Lino-Silva ◽  
Diana L Xinaxtle
Keyword(s):  
Artificial Intelligence ◽  
Gastrointestinal Tract ◽  
Digital Pathology ◽  
Pathology Laboratory ◽  
Tissue Identification ◽  
Technology Applications ◽  
Artificial Intelligence Technology ◽  
Complex Technology ◽  
New Applications

Artificial intelligence (AI) is a complex technology with a steady flow of new applications, including in the pathology laboratory. Applications of AI in pathology are scarce but increasing; they are based on complex software-based machine learning with deep learning trained by pathologists. Their uses are based on tissue identification on histologic slides for classification into categories of normal, nonneoplastic and neoplastic conditions. Most AI applications are based on digital pathology. This commentary describes the role of AI in the pathological diagnosis of the gastrointestinal tract and provides insights into problems and future applications by answering four fundamental questions.

scholarly journals Data-Driven Analytics Leveraging Artificial Intelligence in the Era of COVID-19: An Insightful Review of Recent Developments

Symmetry ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 16
Author(s):  
Abdul Majeed ◽  
Seong Oun Hwang
Keyword(s):  
Artificial Intelligence ◽  
Personal Data ◽  
General Purpose ◽  
Data Driven ◽  
Healthcare Sector ◽  
Future Research ◽  
Recent Developments ◽  
Technological Developments ◽  
Novel Coronavirus

This paper presents the role of artificial intelligence (AI) and other latest technologies that were employed to fight the recent pandemic (i.e., novel coronavirus disease-2019 (COVID-19)). These technologies assisted the early detection/diagnosis, trends analysis, intervention planning, healthcare burden forecasting, comorbidity analysis, and mitigation and control, to name a few. The key-enablers of these technologies was data that was obtained from heterogeneous sources (i.e., social networks (SN), internet of (medical) things (IoT/IoMT), cellular networks, transport usage, epidemiological investigations, and other digital/sensing platforms). To this end, we provide an insightful overview of the role of data-driven analytics leveraging AI in the era of COVID-19. Specifically, we discuss major services that AI can provide in the context of COVID-19 pandemic based on six grounds, (i) AI role in seven different epidemic containment strategies (a.k.a non-pharmaceutical interventions (NPIs)), (ii) AI role in data life cycle phases employed to control pandemic via digital solutions, (iii) AI role in performing analytics on heterogeneous types of data stemming from the COVID-19 pandemic, (iv) AI role in the healthcare sector in the context of COVID-19 pandemic, (v) general-purpose applications of AI in COVID-19 era, and (vi) AI role in drug design and repurposing (e.g., iteratively aligning protein spikes and applying three/four-fold symmetry to yield a low-resolution candidate template) against COVID-19. Further, we discuss the challenges involved in applying AI to the available data and privacy issues that can arise from personal data transitioning into cyberspace. We also provide a concise overview of other latest technologies that were increasingly applied to limit the spread of the ongoing pandemic. Finally, we discuss the avenues of future research in the respective area. This insightful review aims to highlight existing AI-based technological developments and future research dynamics in this area.

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