The growth and popularity of social media platforms have generated a new social interaction environment thus a new collaboration and communication network among individuals. These platforms own tremendous amount of data about users’ behaviors and sentiments since people create, share or exchange their information, ideas, pictures or video using them. One of these popular platforms is Twitter, which via its voluntary information sharing structure, provides researchers data potential of benefit for their studies. Based on Twitter data, in this study a multilingual sentiment detection framework is proposed to compute European Gross National Happiness (GNH). This framework consists of a novel data collection, filtering and sampling method, and a newly constructed multilingual sentiment detection algorithm for social media big data, and tested with nine European countries (United Kingdom, Germany, Sweden, Turkey, Portugal, The Netherlands, Italy, France and Spain) and their national languages over a six year period. The reliability of the data is checked with peak/troughs comparison for special days from Wikipedia news lists. The validity is checked with a group of correlation analyses with OECD Life Satisfaction survey reports’, Euro-Dollar and other currency exchanges, and national stock market time series data. After validity and reliability confirmations, the European GNH map is drawn for six years. The main problem addressed is to propose a novel multilingual social media sentiment analysis framework for calculating GNH for countries and change the way of OECD type organizations’ survey and interview methodology. Also, it is believed that this framework can serve more detailed results (e.g., daily or hourly sentiments of society in different languages).

E-Learning has been an emerging topic for education world for two decades, and due to this fact; it has been analyzed with all of its dimensions and factors. However, the evaluation and assessment issues of e-learning can be assumed as untouched especially in students’ perspective. Evaluation and assessment concepts of students’ cognitive, affective and behavioral domains have a lot of variables that affect each other. In this study, predictors of students’ actual usage of online education systems and their relations are designed as a new theoretical framework, and analyzed by applying Structural Equation Model (SEM) analysis. For this analysis, an online questionnaire is applied to the students who have been using a uniquely designed online evaluation and assessment system (OEAS) for five years in a governmental high school. As a result of the study, “self-efficacy” and “user interface design” are found as significantly effective on “perceived ease of use”, while “self-efficacy” and “perceived ease of use” have significant influence on “perceived usefulness”. In addition, it is found that actual usage of online evaluation and assessment system is directly and significantly affected from “perceived usefulness”, “technical support” and “service quality”. To sum up, the conclusions of the study, in students’ perspective, are advisable for the educational technologists.

Background: Collaboration across health care professions is critical in efficiently and effectively managing complex and chronic health conditions, yet interprofessional care does not happen automatically. Professional associations have a key role in setting a profession’s agenda, maintaining professional identity, and establishing priorities. The associations’ external communication is commonly undertaken through social media platforms, such as Twitter. Despite the valuable insights potentially available into professional associations through such communication, to date, their messaging has not been examined. Objective: This study aimed to identify the cues disseminated by professional associations that represent 5 health care professions spanning 5 nations. Methods: Using a back-iterative application programming interface methodology, public tweets were sourced from professional associations that represent 5 health care professions that have key roles in community-based health care: general practice, nursing, pharmacy, physiotherapy, and social work. Furthermore, the professional associations spanned Australia, Canada, New Zealand, the United Kingdom, and the United States. A lexical analysis was conducted of the tweets using Leximancer (Leximancer Pty Ltd) to clarify relationships within the discourse. Results: After completing a lexical analysis of 50,638 tweets, 7 key findings were identified. First, the discourse was largely devoid of references to interprofessional care. Second, there was no explicit discourse pertaining to physiotherapists. Third, although all the professions represented in this study support patients, discourse pertaining to general practitioners was most likely to be connected with that pertaining to patients. Fourth, tweets pertaining to pharmacists were most likely to be connected with discourse pertaining to latest and research. Fifth, tweets about social workers were unlikely to be connected with discourse pertaining to health or care. Sixth, notwithstanding a few exceptions, the findings across the different nations were generally similar, suggesting their generality. Seventh and last, tweets pertaining to physiotherapists were most likely to refer to discourse pertaining to profession. Conclusions: The findings indicate that health care professional associations do not use Twitter to disseminate cues that reinforce the importance of interprofessional care. Instead, they largely use this platform to emphasize what they individually deem to be important and advance the interests of their respective professions. Therefore, there is considerable opportunity for professional associations to assert how the profession they represent complements other health care professions and how the professionals they represent can enact interprofessional care for the benefit of patients and carers.

Based in Ankara in Turkey, the independent academic publisher, Akademisyen Publishing House, has been publishing books for almost 30 years. As the directors of Akademisyen Publishing House, we are proud to publish around 2000 books across disciplines so far, especially in Health Sciences. We also publish books in Social Sciences, Educational Sciences, Physical Sciences, and also books on cul-tural and artistic topics.Akademisyen Publishing House has recently commenced the process of pub-lishing books in the international arena with the “Scientific Research Book” series in Turkish and English. The publication process of the books, which is expected to take place in March and September every year, will continue with thematic subtitles across disciplines.

Location-based social applications allow users to share their locations in a rich media context, keep in touch with friends and find new places to explore. Studies that investigate the usage factors of location-based social applications are either qualitative or based on application data. In this study, Foursquare, a highly popular mobile location-based social network, was analysed from the perspective of users. This study contributes to the field by employing E-TAM to identify the effects of perceived usefulness, perceived ease of use, perceived enjoyment and social connection in Foursquare usage within the framework of structural equation modelling. The results of the online survey with 233 responses showed that perceived ease of use and perceived enjoyment have a direct and significant impact on actual Foursquare usage, while social connection indirectly affects. Perceived usefulness, on the other hand, has no impact on the actual usage of Foursquare.