Drawing on Herta Herzog’s most famous text, ‘On Borrowed Experience’ (1941), this chapter highlights Herzog’s choice of methods, challenges the alleged rift between so-called ‘critical’ and ‘administrative’ mass-communication research, and tracks Herzog’s work as an important complement to Lazarsfeld’s and Merton’s famous efforts during the same era. In comparison with these two communication researchers, Herzog had a more cognitive and behavioural approach, influencing not only academic research but also commercial, applied research - not least in the service of advertising and PR agencies. In addition, Herzog contributed a gender perspective, as her studies explicitly focused on the everyday lives of women and their respective media habits. Finally, this chapter broadly summarises the foundations of the so-called ‘uses and gratifications’ model, of which Herzog can be said to have been one of the crucial inventors. Important challenges and shortcomings of this research approach are also highlighted.

Linguistic Explorations of Societies (LES) is an interdisciplinary research project with scholars from the fields of political science, computer science, and computational linguistics. The overarching ambition of LES has been to contribute to the survey-based comparative scholarship by compiling and analyzing online text data within and between languages and countries. To this end, the project has developed an online semantic lexicon, which allows researchers to explore meanings and usages of words in online media across a substantial number of geo-coded languages. The lexicon covers data from approximately 140 language-country combinations and is, to our knowledge, the most extensive free research resource of its kind. Such a resource makes it possible to critically examine survey translations and identify discrepancies in order to modify and improve existing survey methodology, and its unique features further enable Internet researchers to study public debate online from a comparative perspective. In this article, we discuss the social scientific rationale for using online text data as a complement to survey data, and present the natural language processing-based methodology behind the lexicon including its underpinning theory and practical modeling. Finally, we engage in a critical reflection about the challenges of using online text data to gauge public opinion and political behavior across the world.

Digital media infrastructures give rise to texts that are socially interconnected in various forms of complex networks. These mediated phenomena can be analyzed through methods that trace relational data. Social network analysis (SNA) traces interconnections between social nodes, while natural language processing (NLP) traces intralinguistic properties of the text. These methods can be bracketed under the header “social big data.” Empirical and theoretical rigor begs a constructionist understanding of such data. Analysis is inherently perspective-bound; it is rarely a purely objective statistical exercise. Some kind of selection is always made, primarily out of practical necessity. Moreover, the agents observed (network participants producing the texts in question) all tend to make their own encodings, based on observational inferences, situated in the network topology. Recent developments in such methods have, for example, provided social scientific scholars with innovative means to address inconsistencies in comparative surveys in different languages, addressing issues of comparability and measurement equivalence. NLP provides novel, inductive ways of understanding word meanings as a function of their relational placement in syntagmatic and paradigmatic relations, thereby identifying biases in the relative meanings of words. Reflecting on current research projects, the chapter addresses key epistemological challenges in order to improve contextual understanding.