When survey science met web tracking: Presenting an error framework for metered data

A primer on open-source, experimental social media simulation software: Opportunities for misinformation research and beyond

Social media simulation software (SMSS) allows researchers to collect behavioural data on how participants to engage with researcher-specified social media content using natural, interactive social media user interfaces. A notable subset of SMSS allow for experimental observation of how people engage with different types of content or user interfaces. Providing an avenue for collecting causal evidence on how algorithmic recommendation systems and design affordances of social media platforms impact behaviour; particularly online harms like misinformation. This article reviews key similarities and differences between three notable SMSS (The (Mis)information Game, the Mock Social Media Website Tool, and the Truman Platform), provides recommendations for use, and perspectives on the future of SMSS.

The dynamics of political and affective polarisation: Datasets for Spain, Portugal, Italy, Argentina, and Chile (2019-2022)

The TRI-POL project explores the triangle of interactive relationships between affective and ideological polarisation, political distrust, and the politics of party competition. In this project there are two complementary groups of datasets with individual-level survey data and digital trace data collected in five countries: Argentina, Chile, Italy, Portugal and Spain. These datasets are comprised of three waves carried out over a six-month period between late September 2021 and April 2022. In addition, the survey datasets include a series of experiments embedded in the different waves that examine social exposure, polarisation framing, and social sorting. The digital trace datasets include variables on individuals' behaviours and exposure to information received via digital media and social media. This data was collected using a combination of tracking technologies that the interviewees installed in their different devices. This digital trace data is matched with the individual-level survey data. These datasets are especially useful for researchers who wish to explore dynamics of polarisation, political attitudes, and political communication.

Inference with non-probability samples and survey data integration: a science mapping study

In recent years, survey data integration and inference based on non-probability samples have gained considerable attention. Because large probability-based samples can be cost-prohibitive in many instances, combining a probabilistic survey with auxiliary data is appealing to enhance inferences while reducing the survey costs. Also, as new data sources emerge, such as big data, inference and statistical data integration will face new challenges. This study aims to describe and understand the evolution of this research field over the years with an original approach based on text mining and bibliometric analysis. In order to retrieve the publications of interest (books, journal articles, proceedings, etc.), the Scopus database is considered. A collection of 1023 documents is analyzed. Through the use of such methodologies, it is possible to characterize the literature and identify contemporary research trends as well as potential directions for future investigation. We propose a research agenda along with a discussion of the research gaps which need to be addressed.