The Communication and Social Beliefs, Ideologies, Affect, and Stereotypes (BIAS) Research lab in the Department of Communication Studies at Ben-Gurion University of the Negev focuses on exploring the ways in which communication and social biases shape public opinion and behavior in different political and cultural contexts. We explore how two central social factors—communication and social constructions—preserve, reinforce, and moderate public opinion and behavior. In our lab, we rely on different combinations of quantitative and qualitative approaches, including a broad range of quantitative methods—notably, experiments, public opinion polls, and content analysis—as well as qualitative ones, such as textual analysis and participatory observations. Through this multi-methodological perspective, we aim to develop a deeper understanding of the elusive role that mass and digital media, perceptions, and stereotypes play in shaping and constructing public opinion and social behavior. Our work aims to understand the mechanisms by which individuals, social groups, and nations construct and preserve public opinion and behavior during both stable times and times of conflict and crisis (e.g., wars, economic crises, or pandemics). The lab’s current work focuses on comparative studies of political and social groups, such as ultra-Orthodox and former ultra-Orthodox individuals, the LGBT and Queer communities, refugees, immigrants, and nations. In addition, together with Prof. Dr. Pascal Jürgens (Department of Media and Communication Studies, University of Trier, Germany), we are developing an artificial neural network that can automatically detect hate speech and stereotypes in textual media frames. We examine these issues across three specific areas: (a) stereotypes and intergroup communication; (b) media, public opinion, and activism; and (c) media, public opinion, and behavior in times of conflict and crisis.
Explore the research areas in which this equipment has been used. These labels are generated based on the related outputs. Together they form a unique fingerprint.