These computational text analysi s tools can help narrow down which videos are worth more in-depth exploration through close-reading analyses like social semiotics/multimodal research conducted in digital contexts. Focusing on the video transcripts opens the door for computational textual analysis tools that can be used to search for word correlations, frequently used words or phrases, and topics. One way to explore the content of the videos is through their transcripts. But, for analytical purposes, it can be useful to s eparate out a single aspect at a time. Ultimately, any attempt at drawing meaning from YouTube must consider all aspects. The user comments and advertising that appear on the same page as the video may be analyzed as well. There are several aspects of YouTube videos that can be distinctly analyzed : visual imagery, metadata about the video (such as duration and author), soundtracks (and sounds), and transcripts. Exploring YouTube Videos through TranscriptionĪs explained in my prior post, YouTube is multimodal. įor those approaches that require close viewing, computational text analysis of YouTube transcripts can help researchers zero in on salient videos. Cultural analytic approaches may look for visual patterns and disruptions in videos or across genres of videos. As noted by this introduction to using video for research, there are several social science and humanities-based approaches to studying videos, includ ing cultural analytic approaches designed to analyze big video data. The number of videos uploaded to YouTube grows by the minute, and researchers are continuing to develop ways of critically engaging the large quantity of content housed on the platform.
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