Five new exciting projects have been selected to receive seed funding from the Digital Communication lab in 2023! The titles and short abstracts of the projects can be found below.

We are looking forward to the results of these cutting-edge research endeavours:

Critical Beings: A Podcast Study

by dr. Gian Hernandez

This proposed study aims to explore diverse embodiment through the use of innovative digital methods, focusing on podcasting as a medium for science communication (O’Hara, 2020). Criticality has emerged as a vital issue in health and fitness communication; notions of structure and agency remain undertheorized in the field (Lupton, 2009; Tiller et al., 2022; Zoller et al., 2019).  The project utilizes a website for both dissemination and research purposes, on which podcast interviews regarding embodiment, diversity, and health and fitness with prominent experts from diverse backgrounds will be hosted. Transcripts of the recorded conversations will be posted on the platform to be commented on annotatively by audiences interested in critical health and fitness.  Finally, these comments on the transcribed conversations will be analyzed using critical discourse analysis (Wodak & Meyer, 2001) to uncover audience attitudes, perceptions, and engagement with diverse themes within critical health and fitness.

A cross-platform, multi-modal investigation into political moral appeals

by dr. Frederic Hopp and dr. Linda Bos

Personalization over-time or over-time personalization? A study on the within- and between-session personalization effects of conversational agent recommendations

by dr. Carolin Ischen, dr. Theo Araujo, prof. dr. Jochen Peter and dr. Alain Starke

Conversational agents (CAs) can make personalized product- or service-related recommendations based on user input, and allow for repeated interactions with their users over time. This study distinguishes between within-session effects which refer to the (longitudinal) effects of one-shot personalized recommendations, and between-session effects which refer to the effects of a CA remembering user input from previous interactions (conversational memory). We aim to test the persuasive effects of these two types of personalization. This project makes a methodological contribution: It extends our conversational agent research toolkit by (1) integrating recommender systems and (2) working with conversational memory over time.

Facts to you, opinions to me: Examining annotation biases in a crowdsourcing study

by Zilin Lin, dr. Susan Vermeer and dr. Anne Kroon

Machine learning has been thriving in the field of communication science. Yet, it should be noted that decent model performance could only be possible to achieve when there is an ample amount of training data with correct annotation. Such model input, unfortunately, is sometimes difficult to obtain, due to the trade-off between quality and quantity within a reasonable research budget and timeframe. In our study, we would like to explore the potential of crowdsourcing as an approach to providing accurate model input. Specifically, we investigate whether annotation biases exist, and if so, whether they are associated with different individual characteristics.

Moved to Comment: Analyzing Social Information Created in Response to Emotional Corporate Films

by dr. Marthe Möller and dr. Joanna Strycharz

Comments written in response to social media content can tell a lot about how people experience this content. The goal of the present project is to use social media comments to detect users’ entertainment experiences in response to social media messages. It does so by analyzing the comments posted in response to emotional corporate films in particular. This way, the project aims to add to the methods that scholars have to measure viewers’ experiences of online entertainment content. In addition, by comparing this novel way of measuring entertainment experiences to more established methods for measuring entertainment experiences (i.e., surveys), the project aims to advance our methodological understanding of different approaches to studying entertainment experiences.

Congratulations to all receivers!

The Digital Communication Methods Lab and Amsterdam School of Communication Research (ASCoR) is looking for a 2-year post-doctoral researcher.

This postdoctoral position focuses on research aimed at advancing computational methods for communication science (e.g., automated content analysis). Technological advancements enable communication scientists to collect different types of data (e.g., through scraping social media data, gathering data through digital agents, receiving data through data donations). Introduction of these novel data collection methods results in availability of large quantities of data that come in various formats (e.g., text data, visual data). This brings on methodological challenges of analyzing such data. In sum, communication researchers now have a broad range of novel computational methods at their disposal to gather and analyze large amounts of data that vary in their format. However, there is a lack of knowledge about the usage and validity of these methods. For example, whereas some algorithms are available to analyze visual data, these algorithms have not been validated on data relevant to communication scholars. This postdoctoral position will contribute to advancing the Lab’s methodological and substantive research in this area by conducting research that advances and validates methods aimed at gathering and analyzing data that are relevant to communication scholars.

For complete details, see https://vacatures.uva.nl/UvA/job/Postdoc-Researcher-Focusing-on-Advancing-Methods-for-Multi-Modal-Automated-Content-Analysis/761538502/

For the fourth time, the Digital Communication Methods Lab  proudly hosts CONVERSATIONS, the International Workshop on Chatbot Research. 

More information about the 2022 edition of the workshop can be found here.

Participation is free and open to presenters and non-presenting researchers, students and practitioners