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Over the last decade, text messages have become one of most popular forms of communication. A diverse array of software to enable the exchange of text messages has been developed and deployed on computers and smart phones which is one of reasons for the increased use of text messages for communication purposes. However, there are several disadvantages for communicators when using text messages. For example, in the text-chat environment, there is a lack of trust between communicators (Bos et al., 2002) and communicators may face a high cognitive load (Thirunarayanan et al., 2002). Therefore, we conducted several studies to improve communication between people in the text-chat environment where important elements for communication, such as facial expressions, do not exist. We examined various data collected from people with different levels of interpersonal trust and cognitive load, including chat contents (e.g., the number of assent words used), mouse movements (e.g., distance travelled by the mouse) and physiological signals (skin response). These data proved to be useful indicators for measuring the level of trust of the communicators and the cognitive load to which the communicators were exposed. These findings have implications for enhancing the communication and relationships between communicators in a text-chat environment and will assist system developers to design applications to measure the conditions the communicators are under when they use the text-chat environment to complete tasks in a business or government context and provide them with suitable assistance.In addition to using the previously mentioned data to measure trust and cognitive load, we further examined the text-chat environment by allowing communicators to see the actions of their partners in real time when they were trying to solve tasks. Our results show that when communicators are able to see the behaviors of their partners when they chat in the text-chat environment while completing tasks, it improves the level of interpersonal trust between them. Finally, in this thesis, we examined the effects of cooperation and cognitive load on interpersonal trust. The findings show that trust is significantly improved between communicators in the text-chat environment when the communicators act in a cooperative way and when they are under a low cognitive load.

The aim of this paper is to briefly explore creative thinking in computer science, and compare it to natural sciences, mathematics or engineering. It is also meant as polemics with some theses of the pioneer work under the same title by Daniel Saunders and Paul Thagard because I point to important motivations in computer science the authors do not mention, and give examples of the origins of problems they explicitly deny. Computer science is a very specific field for it relates the abstract, theoretical discipline – mathematics, on the one hand, and engineering, often concerned with very practical tasks of building computers, on the other. It is like engineering in that it is concerned with solving practical problems or implementing solutions, often with strongly financial reasons, e.g. increasing a company's income. It is like mathematics in that is deals with abstract symbols, logical relations, algorithms, computability problems, etc. Saunders and Thagard analyse rich experimental material from historical and contemporary work in computer science and argue that, as opposed to natural sciences, computer science is not concerned with describing and explaining natural phenomena. Now, I argue that there is a field of research in artificial intelligence (which, in turn, is a branch of computer science), called machine discovery, where explanation of natural phenomena, finding experimental laws and explanatory models is the primary goal. This goal is achieved by constructing computer systems whose job is to simulate various processes involved in scientific discovery done by human researchers, and help them in making new discoveries. On the other hand, motivations that give rise to ingenious projects in computer science can be very strange and include curiosity, fun or attempts to be famous out of boring, stable life of a successful programmer in a big corporation. A good example is the phenomenon of open-source software, especially the development of the Linux operating system and its applications when, from economical point of view, Microsoft absolutely dominated the software market of personal computers.

DBLP (https://dblp.org/) is a comprehensive collection of computer science publications from major and minor journals and conference proceedings. From this dump, we remove arXiv preprints. Our dataset consists of 1.9 million publications from 1970 to 2014 that are authored by 1.1 million authors. We have added citations among publications by combining DBLP with the AMiner dataset (https://www.aminer.org/citation) via publication titles and years. There are 6.6 million citations among publications. Author names in DBLP are disambiguated. To infer the gender of authors, we have used a method that combines the results of name-based and image-based gender detection services. Since the accuracy is very low for Chinese and Korean names, we label their gender as unknown to reduce noise in our analysis.

Info and entertainment goes digital -- Lights, cameras, coding: computer science in television and film -- On the air: computer science in radio -- Low tech goes high tech: computer science in publishing -- Reaching the masses: computer science in new media.