Authors:
Gabriela B. Kurtz
1
;
Stéfano de P. Carraro
2
;
Carlos R. G. Teixeira
2
;
Leonardo D. Bandeira
3
;
Bernardo L. Müller
2
;
Roberto Tietzmann
2
;
Milene Silveira
2
and
Isabel Manssour
2
Affiliations:
1
University Canada West, Vancouver, Canada
;
2
Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil
;
3
Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
Keyword(s):
YouTube, Social Media Analysis, Visualization, Streaming, Chat Interaction.
Abstract:
This paper presents StreamVis, an easy-to-use platform that provides stats and visual representations to analyze live chat data from YouTube. StreamVis uses Python and Google’s YouTube Data API for data gathering, combined with libraries such as NLTK for natural language processing, Pandas for data analysis, and Mat-plotlib for visualization. Its interactive dashboard facilitates real-time data visualization through frequency charts, word clouds, and sentiment analysis, providing deep insights into audience engagement patterns. A case study analyzing the NFL’s first game in Brazil broadcast on Cazé TV demonstrates how StreamVis reveals trends in audience interactions during critical moments, like game highlights and performances. StreamVis is different from previous tools because it has a user-friendly interface, enabling non-technical users (such as journalists and other media professionals) to perform complex data analysis with a large volume of content, helping them to understand
how live chat dynamics influence media consumption.
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