Over the past decade, the online video-sharing platform, YouTube, has become increasingly popular. In our project, we will be analyzing characteristics of a trending (or viral) video. We will be using the `youtube` dataset found on data.world (https://data.world/iamdilan/youtube-dataset) that includes trending video data from 2017 and 2018. This data set has 161470 records and 17 variables. The variables in this dataset are: "video_id", "trending_date", "title, "channel_title", "category_id" "publish_date", "time_frame", "published_day_of_week", "publish_country", "tags", "views", "likes", "dislikes", "comment_count", "comments_disabled", "ratings_disabled", and "video_error_or_removed". The variables have various data types that we will be using in our analysis, including character, integer, boolean, and factors. The focus of our analysis will be on four topics. First we will focus on the titles of trending videos and analyze to see if there are patterns in the length, amount of capital/lowercase letters, and special characters. Next, we will look at the duration of the videos and their amounts of likes/dislikes/comments. After that, we will focus on the posting times and locations, and finally we will investigate the most popular channels according to the trending video data and what categories of videos are the most popular.