文章基本信息

标题：Autoethnography on Researcher Profile Cultivation
本地全文：下载
作者：Małgorzata Pańkowska
期刊名称：Information
电子版ISSN：2078-2489
出版年度：2022
卷号：13
期号：3
页码：154
DOI：10.3390/info13030154
语种：English
出版社：MDPI Publishing
摘要：Information Communication Technology (ICT) and social networks have significant impact on everyday life. One the one hand, Internet users enjoy promoting themselves and feel free to disseminate information about themselves through websites and social networks, but on the other hand, people feel forced to reveal information about them on the Internet. Web technologies enable self-promotion for many reasons, i.e., social relations development, acquiring a new job, or research career support. This paper concerns autoethnography application for social science researcher profile cultivation. Autoethnography belongs to qualitative methods and focuses on deep analysis of experiences and competencies in a narrative way. In this study, autoethnography is self-reflection for personal development strategy. This study methodology includes the literature survey and case study. The Literature Survey (LS) on autoethnographic research is included to answer the question for what purposes autoethnography is applied. In the case study, the author proposes to expand autoethnography and presents that beyond stories, statistical data can be used to reveal researcher’s experiences and personality, and data anonymization is a solution for privacy protection in autoethnographic research. The results indicate that perception of individual profile is significantly influenced by ICT, Internet services, and social networks platforms and portals. Contemporary researchers are evaluated by Web statistical measures. The researcher’s profiling is much more complex and statistical measures and metrics provide a general view of the researcher. Application of statistical measures leads to concluding on general competencies of the researcher and precludes a deep focus on local scientific specificity of the researcher. This paper has added value because of presenting the academic community integration with the Internet social networks, e.g., Facebook, LinkedIn, or SciVal. The paper emphasizes transparency and visibility of researchers’ profiles, as well as the necessity to analyze their activities and publications in academic community context and in comparisons with others.