This lecture calls for a reflection on new ethnographic methods by holding a media diary pratices (Cavalcante, 2021) presenting features of the open source software developed in Python, Qualichat. Understands interactions as a perception of Goffmanian’s frame analysis. It becomes necessary when media repertoires appear in a constellation of actors (Couldry & Hepp, 2020) that organize their realities through thematic frameworks. Through frames, the human and the nonhuman are joined in the complexity of deep mediatized interactions. The hypothesis to be used is Erving Goffman's analysis (1974), which contributes to the development of thematic framings (frames of relevance) in WhatsApp groups. This lecturer points out paths for frames of relevance based on qualitative and quantitative analysis of WhatsApp interaction anchoring delineations. The features developed by the software created by the researcher (Qualichat) materialize public opinion in WhatsApp groups can be grouped as latencies of fabrications and laminations, allowing the ethnographic content to be guided by further quantitative encadecences. An index of the ideal types of groups, based on Ernest Manheim's socio-historical studies will be presented in the lecture, updating new tools for investigating public opinion, the opinion that emerges in small group bonds.
Fernando Cavalcante is Associate Professor of Media and Communication Research at the Department of Communication at UNI7, Fortaleza, Brazil. He is also the coordinator of the Communication Research Center (NUPECOM) and member of the UNI7 Distance Learning Implementation Board. He is founder and senior researcher of the Ernst Manheim Public Opinion Laboratory. His main research focus is on the development of a software project for conversation analysis and interaction in instantaneous communication networks (WhatsApp) and focus group research analysis with Qualitative Data Analysis Software (ATLAS.ti).
The event is hybrid and can be accessed at the following link: https://uni-bremen.zoom.us/j/97514306782?pwd=MXVNSEZraDI1Yk90ZDNUcnMrdHVOQT09