Learning Social Relation Traits from Face Images

Social relation defines the association, e.g, warm, friendliness, and dominance, between two or more people. Motivated by psychological studies, we investigate if such fine-grained and high-level relation traits can be characterised and quantified from face images in the wild. To address this challenging problem we propose a deep model that learns a rich face representation to capture gender, expression, head pose, and age-related attributes, and then performs pairwise-face reasoning for relation prediction. To learn from heterogeneous attribute sources, we formulate a new network architecture with a bridging layer to leverage the inherent correspondences among these datasets. It can also cope with missing target attribute labels. Extensive experiments show that our approach is effective for fine-grained social relation learning in images and videos.Comment: To appear in International Conference on Computer Vision (ICCV) 201

Some Sources of Misunderstandings in Intercultural Business Communication

It is always a big challenge for all types of companies anywhere in the world to survive in the globalised and accelerated world. Their primary objective is to stay competitive, keep or even enlarge their market share while keeping their costs at a minimum level. These corporations often cross borders and operate on a multinational level. In order to do that successfully they need flexible workforce: people who have a high level of intercultural competencies and can help their corporations to achieve their aim of profit maximising. It is widely accepted that culture and languages are among the most significant impacts on intercultural communication. In this paper first I am going to interpret intercultural communication and the role of culture and then look at different intercultural skills and the role of languages in intercultural communication. Some areas that might cause problems in intercultural business communication will also be described

The lexical fallacy in emotion research: Mistaking vernacular words for psychological entities.

Vernacular lexemes appear self-evident, so we unwittingly reify them. But the words and phrases of natural languages comprise a treacherous basis for identifying valid psychological constructs, as I illustrate in emotion research. Like other vernacular lexemes, the emotion labels in natural languages do not have definite, stable, mutually transparent meanings, and any one vernacular word may be used to denote multiple scientifically distinct entities. In addition, the consequential choice of one lexeme to name a scientific construct rather than any of its partial synonyms is often arbitrary. Furthermore, a given vernacular lexeme from any one of the world's 7000 languages rarely maps one-to-one into an exactly corresponding vernacular lexeme in other languages. Words related to anger in different languages illustrate this. Since each language constitutes a distinct taxonomy of things in the world, most or all languages must fail to cut nature at its joints. In short, it is pernicious to use one language's dictionary as the source of psychological constructs. So scientists need to coin new technical names for scientifically derived constructs-names precisely defined in terms of the constellation of features or components that characterize the constructs they denote. The development of the kama muta construct illustrates one way to go about this. Kama muta is the emotion evoked by sudden intensification of communal sharing-universally experienced but not isomorphic with any vernacular lexeme such as heart warming, moving, touching, collective pride, tender, nostalgic, sentimental, Awww-so cute!. (PsycINFO Database Record (c) 2019 APA, all rights reserved)

Doctor of Philosophy

dissertationWith much of the focus on empathy coming from the professional contexts of psychology and the medical field, this study moves the scope of empathy research towards understanding how empathic communication is experienced in the personal lives of individuals. A constructivist's approach to grounded theory is used to explore the way a group of students experienced and learned communicative empathy over the course of a semester. Using symbolic interaction as a theoretical lens, this research project centers on two aspects of empathy. First, using empathy journals as a means to access students' personal experiences, it calls attention to the communicative behaviors that the students perceived as paramount to creating an empathic interaction. Second, it highlights how the students' working models of empathy changed over the course of the semester. Drawing on message design logic, the analysis shows that at the outset of the course, the students drew on linear models of communication and a predominantly expressive design logic to conceptualize empathy. By the end of the semester, the majority of the students developed more sophisticated design logics and articulated a view of empathy that was rooted in a transactional model of communication. The limitations and implications of this research are discussed in the final chapter