Content analysis of video data using text and voice analysis: case of YouTube videos related to COVID-19

Purpose The objective of this research is to examine the content of videos on YouTube and investigate the factors that contribute to their popularity and impact through viewer engagement. Another objective of this research is to demonstrate the value of advanced analytical tools like voice analysis and text analysis to carry out content analysis of user generated content on social media. Design/methodology/approach Using a web scrapping approach, a sample ( N = 831) of videos was downloaded from a popular social media site (YouTube) along with descriptive data about their usage and popularity. Text analysis using Linguistic Inquiry and Word Count 2015 (LIWC2015) was used to carry out content analysis of videos. Soundtracks of videos were also extracted and analyzed using voice analysis program, VokaturiPlus. Findings Results show that there is a difference in the focus in titles, descriptions and contents of YouTube videos about the coronavirus. People emphasize certain aspects of the video in titles and descriptions to attract viewers and then change the emphasis in the content of videos. Factors that contribute to viewer engagement are also discussed along with implications of the findings. The research also demonstrated the value of advanced analytical tools like voice analysis and text analysis to gain more insights into user-generated content on social media. Originality/value This research contributes to the field of qualitative research methodology by introducing a unique approach to quantify qualitative data and combine it with quantitative data to carry out content analysis of YouTube videos. This research also contributes by providing insights into how information about COVID-19 is spread on YouTube.