Search

Sosyal ağ siteleri (SAS), bireylerin hem çevrimdışı hayatta hem de çevrimiçi ortamda tanıdıklarının bir araya geldiği yerlerdir. Kullanıcı olarak bireyler SAS’ta yer alan profilleri üzerinden çeşitli paylaşımlar yapmaktadır. Instagram, hem dünyada hem de Türkiye’de popüler olan bir SAS’tır. Instagram, 2018 yılından bu yana hikâye paylaşımlarına ‘yakın arkadaş’ özelliğini getirmiştir. Bu özellik kullanıcıların yayınladıkları hikâyelerin sadece belirli bir grup tarafından görüntülenmesini sağlamaktadır. Bu çalışmanın amacı, Instagram’da ‘yakın arkadaş’ özelliği kullanımının nedenlerini ve bu özelliğin kullanımının nasıl algılandığını anlamaktır. Araştırmada nitel yöntem uygulamalarından fenomenolojik desen kullanılmıştır ve amaçlı örneklem tercih edilmiştir. Veriler iki aşamalı olarak toplanmıştır. Birinci aşamada 200 kişiye ulaşılmış ve Google Formlar’da oluşturulan bir soru formu ile nitel veriler toplanmıştır. İkinci aşamada ise birinci aşamaya katılan 15 kişi ile derinlemesine görüşme yapılmıştır. Araştırma sonucunda elde edilen verilerin bazılarını şöyle ifade etmek mümkündür: ‘Yakın arkadaş’ özelliğini kullanan katılımcıların Instagram’da ‘yakın arkadaş’ listesinde yer alan kişiler sadece çevrimdışı hayatta yakın arkadaşı olan kişiler değildir. Katılımcılar ‘yakın arkadaş’ listelerini belirlerken kapsamaya ya da dışarıda bırakmaya odaklanmaktadır. Kapsama için öne çıkan temalar şöyledir: İdeolojik yakınlık, benzer hayat tarzı, yargılanmama. Dışarıda bırakma nedenleri ise aile / akrabalar, iş ilişkileridir. Katılımcılar başkalarının ‘yakın arkadaş’ belirlemelerine ilişkin gözlemlerinde ise hayat tarzı ve bununla bağlantılı olarak alkol kullanımını belirtmişlerdir. Katılımcılar, genellikle başkalarının ‘yakın arkadaş’ listesinde olmaktan rahatsız olmadıklarını ifade etmiş ve ‘yakın arkadaş’ listesini güvenli alan olarak tanımlamıştır. ‘Yakın arkadaş’ özelliğini kullanmayan katılımcılar ise başkasının listesinde bulunmaktan memnun olmadıklarını ya da nötr olduklarını söylemiştir.

Sharing on social media has brought out different communicative affordances in order to construct individuals’ identities. In this study, the relationship between real and ideal selves was examined with regard to variables like gender, age, Instagram usage habits, and purposes. In order to reveal the bases of such changes in our self-representation, Adler’s individual psychology theory and Goffman’s theories on identity and self-representation were reflected on the results of a questionnaire including the Ideal and Real Self-Concept Scale generated by Waugh (2001) and adapted in the context of Turkey by Kapıkıran (2004). In this study, the questionnaire consists of questions on demographic features, Instagram usage habits, and it was conducted with generation-y Instagram users in Turkey, who were recruited via convenience and selective accidental sampling. The results indicated that there is a correlation between individuals’ academic self-concept, social self-concept, and self-presentation as subscales. In addition to this, the data revealed that the current presentations of real and ideal selves rarely exist based on academic self-concept and social self-concept. Within this study, how generation-y Instagram users mix and integrate their real or ideal selves is discussed, and some subtle cues to represent their selves on social media platforms are revealed.

Security means the state of being free from danger, risk or threat. In social sciences, human security is an emerging paradigm shift concerning a person-centered, multi-disciplinary understanding of security involving a number of studies and human rights. According to Amartya Sen 2000 , “human security” is a keyword referring comprehensively everything free of the menaces that threaten the survival, daily lives, and dignity of individuals and to strengthening the efforts to confront these threats. On the other hand, “human insecurity” as a term stands for defining various situations where conflicts lead to perception of deprivation of some-kind, among certain people, in a given context Sirkeci, 2009 . Human insecurity affects migration movements in a way with the connection of 3Ds: namely democratic, development and demographic deficits. Accordingly, it is claimed that recent developments, the attempted coup on July 15, 2016 and the aftermath have made Turkey as a seemingly insecure place in reference to these 3Ds facilitating migration movements in and/or from the country. Sirkeci, 2017 According to the reports of Eurostat published in 2016, asylum applications filed by citizens of Turkey in European countries reached at 3779 in the third quarter comparing to the same quarter of 2015 at 985. After the attempted coup, this tendency seems on the rise, which actually signals us the fact that human insecurity perceptions among citizens. To evaluate this hypothesis, Twitter, as a public social media platform, based on the hashtags used by Turkish people, such as #avrupabirligi and #avrupabirliği in English “european ” was evaluated within the methodology content analysis.

Abstract Background As antibiotic resistance creates a significant global health threat, we need not only to accelerate the development of novel antibiotics but also to develop better treatment strategies using existing drugs to improve their efficacy and prevent the selection of further resistance. We require new tools to rationally design dosing regimens from data collected in early phases of antibiotic and dosing development. Mathematical models such as mechanistic pharmacodynamic drug-target binding explain mechanistic details of how the given drug concentration affects its targeted bacteria. However, there are no available tools in the literature that allow non-quantitative scientists to develop computational models to simulate antibiotic-target binding and its effects on bacteria. Results In this work, we have devised an extension of a mechanistic binding-kinetic model to incorporate clinical drug concentration data. Based on the extended model, we develop a novel and interactive web-based tool that allows non-quantitative scientists to create and visualize their own computational models of bacterial antibiotic target-binding based on their considered drugs and bacteria. We also demonstrate how Rifampicin affects bacterial populations of Tuberculosis bacteria using our vCOMBAT tool. Conclusions The vCOMBAT online tool is publicly available at https://combat-bacteria.org/ .