This paper illustrates how to implement state space grid analysis for analyzing the back-and-forth multi-turn dynamics that manifest in dyadic conversations. In doing so, we contribute to a dynamic...

This paper demonstrates the performance of the Joint Sentiment Topic model (JST) and the reversed Joint Sentiment Topic model (rJST) in measuring sentiment in political speeches, comparing them aga...

Digital trace data is an increasingly popular alternative to surveys, often considered as the gold standard. This study critically assesses the use of web tracking data to study online media exposu...

Named Entity Recognition (NER) is a supervised machine learning task that finds various applications in automated content analysis, as the identification of entities is vital for understanding publ...

Language models like BERT or GPT are becoming increasingly popular measurement tools, but are the measurements they produce valid? Literature suggests that there is still a relevant gap between the...

Search engines play a crucial role in today’s information environment. Yet, political and news-related (PNR) search engine use remains understudied, mainly due to the lack of suitable measurement m...

Researchers often invoke individual-level correlations (correlations between properties of individuals) as a basis for message-level claims (claims about properties of messages). For example: “Peop...

Named Entity Recognition (NER) is a crucial task in natural language processing and has a wide range of applications in communication science. However, there is a lack of systematic evaluations of ...

Published in Communication Methods and Measures (Vol. 18, No. 1, 2024)

This note intends to complement the recent discussion in Hayes and Coutts (2020) by focusing on (i) the loading equality condition for the population identity of coefficient alpha and reliability o...

Topic Modelling has established itself as one of the major text-as-data methodologies within the social sciences in general, and in communications science, in particular. The core strength of TM ap...

Automated classifiers (ACs), often built via supervised machine learning (SML), can categorize large, statistically powerful samples of data ranging from text to images and video. They have become ...

Published in Communication Methods and Measures (Ahead of Print, 2023)

In this paper, we propose a new strategy for classifying evaluations in large text corpora, using supervised machine learning (SML). Departing from a conceptual and methodological critique of the u...

We propose a new method that embeds speakers into a spatial representation according to the linguistic similarity of their contributions to a debate. Such “speaker landscapes” can be constructed qu...

Communication research frequently applies computational text analysis methods (CTAM) to detect and measure social science constructs. However, the validity of these measures can be difficult to ass...

A pressing societal and scientific question is how social media use affects our cognitions, emotions, and behaviors. To answer this question, fine-grained insight into the content of individuals’ s...

To advance our understanding of social media effects, it is crucial to incorporate the increasingly prevalent visual media into our investigation. In this article, we discuss the theoretical opport...

Published in Communication Methods and Measures (Vol. 17, No. 4, 2023)

Despite the increasing use of digital media data in communication research, a central challenge persists – retrieving data with maximal accuracy and coverage. Our investigation of keyword-based dat...

The availability of individual-level digital trace data offers exciting new ways to study media uses and effects based on the actual content that people encountered. In this article, we argue that ...

Linkage analysis, i.e. linking media exposure, content, and surveys, has been a powerful tool to assess media effects. However, the development of online communication and the advent of social medi...

The need for privacy has been gaining importance in various disciplines and areas of communication, including computer-mediated, interpersonal, and health communication. These disciplines require r...

Women of Color (WoC) in science, technology, engineering, and math (STEM) leave doctoral programs at disproportionately high rates. Supportive mentorship is key to increasing belonging and rates of...

Conversations between people are where, among other things, stressors are amplified and attenuated, conflicts are entrenched and resolved, and goals are advanced and thwarted. What happens in dyads...

The present research examined how value-free and value-driven measures of argument strength (MAS) can be computationally extracted using a theory-driven approach at scale in a naturalistic setting ...

ABSTRACT The empirical identification of frames drawing on automated text analysis has been discussed intensely with regard to the validity of measurements. Adding to an evolving discussion on automated frame identification, we systematically contrast different machine-learning approaches with a manually coded gold standard to shed light on the implications of using one or the other: (1) topic modeling

The cognitive-emotional theory of esteem support messages (CETESM) posits that esteem support can enhance recipients’ state self-esteem after an acute threat. To test the CETESM and other supportiv...

Understanding the implications of aggressive political debate style amid corrosive modes of campaign politics requires fine-grained analyses of political performance, attending to multiple communic...

Informed by the dynamic dyadic systems perspective on analyzing conversational data, this study uses sequence analysis to illuminate turn patterns that characterize parents’ emotion coaching/dismis...

ABSTRACT In persuasion message effects research, two kinds of research design are common. One compares the persuasiveness of two different advocacy messages on the same topic. The other compares the persuasiveness of an advocacy message against a no-advocacy-message control condition. Because these two designs contain different comparisons they underwrite different claims, but the designs – and their

Dispositional communication competencies can be assessed in (a) a generic form that does not include any reference to a particular medium of interaction or in (b) a communication medium-specific ve...

More adults are dating in later life, yet little is known regarding how older adults navigate conflict in their newly formed relationships. Given theories suggesting that older adults are especiall...

Although turn-level dynamics involving the back-and-forth exchange of talk between support seekers and providers form the foundation for supportive conversations, they have largely been overlooked ...

Ephemeral digital trace data can decrease the completeness, reproducibility, and reliability of social media datasets. Systematic post deletions thus potentially bias the results of computational m...

ABSTRACT Using data donations to collect digital trace data holds great potential for communication research, which has not yet been fully realized. Besides limited awareness and expertise among researchers, a central challenge is to motivate people to donate their personal data. Therefore, this article investigates which factors affect people’s willingness to donate across different platforms and

In social media effects research, the role of specific social media content is understudied, in part attributable to the fact that communication science previously lacked methods to access social m...

ABSTRACT Recently, latent variable mixture modeling has gained traction in many disciplines, given its unique ability to discover unknown groups within a broader population. Indeed, this method assumes that a finite number of mixtures (i.e. unknown groups) exist within the population and can be discovered by evaluating participants’ response patterns to a set of manifest indicators. Despite the intuitive

Published in Communication Methods and Measures (Vol. 17, No. 2, 2023)

ABSTRACT As more computational communication researchers turn to supervised machine learning methods for text classification, we note the challenge in implementing such techniques within an imbalanced dataset. Such issues are critical in our domain, where, in many cases, researchers attempt to identify and study theoretically interesting categories that can be rare in a target corpus. Specifically

ABSTRACT Incivility in online discussions has become an important issue in political communication research. Instruments and tools for the automated analysis of uncivil content, however, are rare, especially for non-English user-generated text. In this study, we present a) an extensive dictionary (DIKI - Diktionär für Inzivilität, English: Dictionary for Incivility) to detect incivility in German-language

ABSTRACT Topic modeling has become an effective tool for communication scholars to explore large amounts of texts. However, empirical studies applying topic modeling often face the critical question of making meaningful theoretical contributions. In this study, we highlighted the importance of theoretical underpinning, the research design, and the methodological details of topic modeling studies. We

ABSTRACT Communication research often focuses on processes of communication, such as how messages impact individuals over time or how interpersonal relationships develop and change. Despite their importance, these change processes are often implicit in much theoretical and empirical work in communication. Intensive longitudinal data are becoming increasingly feasible to collect and, when coupled with

As chatbots are gaining more popularity than ever, they have recently been considered as interesting tools for survey administration in social science research. To explore this idea, we investigate...

ABSTRACT Supervised machine learning (SML) provides us with tools to efficiently scrutinize large corpora of communication texts. Yet, setting up such a tool involves plenty of decisions starting with the data needed for training, the selection of an algorithm, and the details of model training. We aim at establishing a firm link between communication research tasks and the corresponding state-of-the-art

ABSTRACT Although theory and research have discussed identity insecurity as a factor that influences intercultural communication behaviors, no reliable measure has been presented to capture this construct. This paper reports results from three studies designed to test and validate a new measure of identity insecurity. Study 1 (N = 173) included item generation and exploratory factor analysis, revealing

ABSTRACT This paper presents a critical discussion of the processing, reliability and implications of free big data repositories. We argue that big data is not only the starting point of scientific analyses but also the outcome of a long string of invisible or semi-visible tasks, often masked by the fetish of size that supposedly lends validity to big data. We unpack these notions by illustrating the

ABSTRACT Internet memes are a fundamental aspect of digital culture. Despite being individual expressions, they vastly transcend the individual level as windows into and vehicles for wide-stretching social, cultural, and political narratives. Empirical research into meme culture is thriving, yet particularly compartmentalized. In the humanities and social sciences, most efforts involve in-depth linguistic

ABSTRACT Studies assessing the effects of social media use are largely based on measures of time spent on social media. In recent years, scholars increasingly ask for more insights in social media activities and content people engage with. Data Download Packages (DDPs), the archives of social media platforms that each European user has the right to download, provide a new and promising method to collect

ABSTRACT This paper discusses ‘strong-form’ frequentist testing as a useful complement to null hypothesis testing in communication science. In a ‘strong-form’ set-up a researcher defines a hypothetical effect size of (minimal) theoretical interest and assesses to what extent her findings falsify or corroborate that particular hypothesis. We argue that the idea of ‘strong-form’ testing aligns closely

ABSTRACT Communication Quality Analysis (CQA) is a rigorous transcript-based coding method for assessing clinical communication quality. We compared the resource-intensive transcript-based version with a streamlined real-time version of the method with respect to feasibility, validity, reliability, and association with traditional measures of communication quality. Simulated conversations between 108

ABSTRACT Insufficient statistical reporting practices (ISRPs) involve failure to report effect sizes or the information necessary to compute them in quantitative research. ISRPs can present problems for advancing knowledge in the field of Communication. Because, among other issues, studies containing ISRPs cannot be included in meta-analytic reviews, this practice undermines our ability to quantitatively

ABSTRACT Although media and communication scholars have suggested various analytical methods for measuring and comparing news audience polarization across countries, we lack a systematic assessment of the metrics produced by these techniques. Using survey data from the 2016 Reuters Institute Digital News Report on news use in 26 countries, we address this gap through a resampling simulation experiment

ABSTRACT Digital trace data have become one of the central pillars of media research methods. Despite the opportunities for better understanding individual users’ true behaviors in the personalized media environment, many scholars have pointed out the potential for bias in trace data collections, questioning the generalizability of findings based on them. In this study, we propose two statistical bias

ABSTRACT We present the Conversation Analysis Modeling Schema (CAMS), a novel dialogue labeling schema that combines the Conversation Analysis concept of Adjacency Pairs, with Dialogue Acts. The aim is to capture both the semantic and syntactic structure of dialogue, in a format that is independent of the domain or topic, and which facilitates the computational modeling of dialogue. A labeling task

ABSTRACT We identify three gaps that limit the utility and obstruct the progress of computational text analysis methods (CTAM) for social science research. First, we contend that CTAM development has prioritized technological over validity concerns, giving limited attention to the operationalization of social scientific measurements. Second, we identify a mismatch between CTAMs’ focus on extracting

ABSTRACT Dictionary-based approaches to computational text analysis have been shown to perform relatively poorly, particularly when the dictionaries rely on simple bags of words, are not specified for the domain under study, and add word scores without weighting. While machine learning approaches usually perform better, they offer little insight into (a) which of the assumptions underlying dictionary

ABSTRACT Agent-based computational models create virtual laboratories in which to formalize and simulate dynamic, multi-level theories of communication. They allow the systematic development of thought experiments, and they improve our understanding of the generative mechanisms that underlie patterns observed in empirical data. Simulation models help explore hypothetical and unprecedented scenarios

ABSTRACT In light of the widespread use of big data analytics, internet users are increasingly confronted with algorithmic decision-making. Developing algorithm literacy is thus crucial to empower users to successfully navigate digital environments. In this paper, we present the development and validation of an algorithm literacy scale that consists of two interrelated dimensions: 1) awareness of algorithms

ABSTRACT In communication research, topic modeling is primarily used for discovering systematic patterns in monolingual text corpora. To advance the usage, we provide an overview of recently presented strategies to extract topics from multilingual text collections for the purpose of comparative research. Moreover, we discuss, demonstrate, and facilitate the usability of the “Polylingual Topic Model”