An Empirical Study of the Textual Content of Online Videos

Fuelled by the advancements in multimedia technologies, users across the world have witnessed the proliferation of online videos. Compared with the visual content of videos, the textual content, for example, titles, tags, or descriptions, is more broadly exploited in the real-world video data mining or information retrieval tasks. To enhance the understanding of videos, and improve the performance of tasks such as automatic video annotation, video clustering, and cross-modal tag cleansing, the textual and visual content of videos have been combined, through various models. However, the absence of an empirical study on the properties of these contents makes them less solid to gain satisfactory performance. Therefore, in this paper, we conduct this study to verify the properties of textual content and draw insights from the analysis to promote further development in video data mining that combines the two contents.