The Implementation of Online Training for Library Employees as an Activity Increasing Competencies in the Promotion of Culture on the Internet

Thesis / purpose of the article ‒ The aim of the article is to analyse the process of on-line training for library employees as an activity increasing competencies in the field of promoting culture on the Internet. Research methods ‒ The training process concerning areas that have a direct or indirect impact on the subsequent activities of library employees on the Internet is discussed. Various forms of online training are indicated, among which priority is given to the division into synchronous and asynchronous training. Results and conclusions ‒ Libraries, as cultural institutions, play a special role in providing access to information and cultural events. This scope of activity is of exceptional importance in the case of local communities, in particular those located outside large urban centres. Therefore, business continuity is very important, even in unusual situations such as the COVID-19 pandemic

A DIVISION OF LABOR: THE ROLE OF BIG DATA ANALYSIS IN THE REPERTOIRE OF INTERNET RESEARCH METHODS

In recent years, large-scale analysis of log data from digital devices - often termed ""big data analysis"" (Lazer, Kennedy, King, & Vespignani, 2014) - have taken hold in the field of internet research. Through Application Programming Interfaces (APIs) and commercial measurement, scholars have been able to analyze social media users (Freelon 2014) and web audiences (Taneja, 2016) on an uprecedented scale. And by developing digital research tools, scholars have been able to track individuals across websites (Menchen-Trevino, 2013) and mobile applications (Ørmen & Thorhauge 2015) in greater detail than ever before. Big data analysis holds unique potential for studying communication in depth and across many individuals (see e.g. Boase & Ling, 2013; Prior, 2013). At the same time, this approach introduces new methodological challenges in the transparency of data collection (Webster, 2014), sampling of participants and validity of conclusions (Rieder, Abdulla, Poell, Woltering, & Zack, 2015). Firstly, data aggregation is typically designed for commercial rather than academic purposes. The type of data included as well as how it is presented depend in large part on the business interests of measurement and advertisement companies (Webster, 2014). Secondly, when relying on this kind of secondary data it can be difficult to validate the output or techniques used to generate the data (Rieder, Abdulla, Poell, Woltering, & Zack, 2015). Thirdly, often the unit of analysis is media-centric, taking specific websites or social network pages as the empirical basis instead of individual users (Taneja, 2016). This makes it hard to untangle the behavior of real-world users from the aggregate trends. Lastly, variations in what users do might be so large that it is necessary to move from the aggregate to smaller groups of users to make meaningful inferences (Welles, 2014). Internet research is thus faced with a new research approach in big data analysis with potentials and perils that need to be discussed in combination with traditional approaches. This panel explores the role of big data analysis in relation to the wider repertoire of methods in internet research. The panel comprises four presentations that each sheds light on the complementarity of big data analysis with more traditional qualitative and quantitative methods. The first presentation opens the discussion with an overview of strategies for combining digital traces and commercial audience data with qualitative interviews and quantitative survey methods. The next presentation explores the potential of trace data to improve upon the experimental method. Researcher-collected data enables scholars to operate in a real-world setting, in contrast to a research lab, while obtaining informed consent from participants. The third presentation argues that large-scale audience data provide a unique perspective on internet use. By integrating census-level information about users with detailed traces of their behavior across websites, commercial audience data combines the strength of surveys and digital trace data respectively. Lastly, the fourth presentation shows how multi-institutional collaboration makes it possible do document social media activity (on Twitter) for a whole country (Australia) in a comprehensive manner. A feat not possible through other methods on a similar scale. Through these four presentations, the panel aims to situate big data analysis in the broader repertoire of internet research methods.

Measurements in E-Business

This chapter is designed to answer two fundamental questions related to research on electronic surveys and measures. First, what are some of the major measures specifically related to e-business? Second, what makes Internet research methods different from off-line research methods? The chapter partly delineates what makes Internet research methods distinctive through its discussion and separation of the most common measures. This separation not only provides the framework for the chapter, but it distinguishes research for understanding the evolving e-consumer from measures related to the new paradigm for e-business strategy. In total, 17 different measures are discussed. The chapter concludes with a discussion of emerging issues in e-business metrics, and possibilities for future research.