Exploring the Frontiers of Digital Social Research: Analysis of Biases in Digital Data and Implications for Online Social Research

The present study titled "Exploring the Frontiers of Digital Social Research: Analysis of Distortions in Digital Data and Implications for Online Social Research" delves into the analysis of distortions that occur in digital data (Rogers, 2015) and their implications for online social research (Delli Paoli & Masullo, 2022). Due to the pervasiveness of digital technologies and the growing role of online communication channels in our everyday lives, researchers have increasingly turned to digital data sources to study social phenomena. However, the accuracy and validity of such data are often compromised by various distortions, posing significant challenges to conducting reliable research. To this end, starting with the Depictions of the framework that Olteanu et.al (2019) use to describe biases and pitfalls while working with social data, this research aims to collect and analyze studies in the field of sociology that use digital data and that have questioned the quality of the data and other issues related to the use of these data to date. Through an extensive review of the existing literature and empirical analysis, the study identifies several sources of bias in digital data, including sampling bias, measurement error, and selection bias. From the empirical point of view, through a literature review we want to extrapolate and study articles in the field of sociology using digital data published on the Web of Science indexing platform. The selection criteria used for article extraction are: 1. Field of study: (Sociology) 2. Publication type (Articles); 3. Language (English); 4. Publication format (Open Access). The words used for extraction are: Digital data, Data quality, Digital traces, Distortion, Reliability, Validity, Generalizability, Trustworthiness, Credibility, Transferability, Confirmability, Biases, Evaluation and Ethics for a total of 129 articles then subjected to quality control by the researchers in order to identify the articles most relevant to the study.