Information Diffusion Dataset on Twitter with User Tweets

We looked at 10,269 users on Twitter and collected their tweets and the follower network from April 2019 to October 2019. We organized tweets with the same hashtag into 29,192 cascades. To find an active community, we first selected 500 popular seed users. Subsequently, we added users who followed these seed users to the target group. After adding more users iteratively for five rounds, we locked the target group. The hashtag is considered as the keyword for each cascade. We filter out cascades with less than 2 or more than 500 participants and those inactive users who appear in less than three different cascades. Besides, in this dataset, we only keep the cascades with hashtags longer than five characters, because some long hashtags placed at the end of tweets may be truncated due to the length limit of the Twitter API. In addition, this dataset also discards cascades with a hashtag containing special characters, such as emojis. The Twitter dataset will be made available on IEEE DataPort after the publication of the manuscript.