The dataset consists of 479 193 tweets each of them contains one of the 31 gesture emoji (different hand configurations) and its skin tone modifier options (e.g. 🙏🙏🏿🙏🏾🙏🏽🙏🏼🙏🏻), posted within 250km from San Jose, CA and within 200km from Los Angeles, CA, in English, during May-August 2021. The dataset can be used to investigate the use of gesture emoji by English-speaking California Twitter users. Python libraries used for collecting tweets and preprocessing: tweepy, re, preprocessor, emoji, regex, string, nltk. The dataset contains 11 columns: preprocessed preprocessed text of the tweet (4 steps) all_emoji lists all emoji in a given tweet hashtags lists all hashtags in a given tweet user_encoded encoded Twitter user name: the first 3 characters of the user name and the first 3 characters of the user's location location_encoded location of the user: "los_angeles", "san_diego", "san_jose", "san_francisco", "fresno", "long_beach", "sacramento", "oakland", "bakersfield", "anaheim", or "other" mention_present checks whether each tweet contains mentions url_present checks whether each tweet contains url preprocess_tweet preprocessing step 1: tokenizing mentions, urls, and hashtags lowercase_tweet preprocessing step 2: lowercasing remove_punct_tweet preprocessing step 3: removing punctuation tokenize_tweet preprocessing step 4: tokenizing The further information on the research project can be found here: https://github.com/mzhukovaucsb/emoji_gestures/