Replication Data for: Not Just Conspiracy Theories: Vaccine Opponents and Proponents add to the COVID-19 ‘Infodemic’ on Twitterdoi:10.7910/DVN/9ICICYHarvard Dataverse2020-08-261Broniatowski, David, 2020, "Replication Data for: Not Just Conspiracy Theories: Vaccine Opponents and Proponents add to the COVID-19 ‘Infodemic’ on Twitter", https://doi.org/10.7910/DVN/9ICICY, Harvard Dataverse, V1Replication Data for: Not Just Conspiracy Theories: Vaccine Opponents and Proponents add to the COVID-19 ‘Infodemic’ on Twitterdoi:10.7910/DVN/9ICICYBroniatowski, DavidHarvard DataverseBroniatowski, DavidBroniatowski, David2020-08-25Computer and Information ScienceMedicine, Health and Life SciencesSocial SciencesThese files contain the data required to replicate all findings in the referenced paper. Files include: 1) 2000_Account_IDs.txt -- a tab-separated text file listing the top 2000 accounts mentioning vaccine-related keywords in CY 2019. 2) users_ids.csv -- a comma-separated file listing all tweet IDs containing coronavirus-related keywords generated by each of the 2000 accounts. The first entry on each line is a username, followed by a list of tweet IDs. 3) users_botscores.txt -- a tab-separated text file listing the bot scores generated from querying Botometer on March 2, 2020. The first entry is the raw (English) bot score and the second entry is the CAP score. 4) corona_topic_keys.txt -- the top 20 words for each of 35 topics generated using the LDA algorithm fit to all tweets listed in users_ids.csv 5) corona_doc_topics.txt -- LDA model topic results fit to each tweet in users_ids.csv. The second column corresponds to the tweet ID, and the following 35 columns are topic proportions for topics 0-34, respectively.<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a>2000_Account_IDs.txtUser ID, retweet count, and annotations for the 2000 most prolific accounts in the vaccine stream Twitter archive for calendar year 2019.text/plaincorona_doc_topics.txtLDA model topic results fit to each tweet in users_ids.csv. The second column corresponds to the tweet ID, and the following 35 columns are topic proportions for topics 0-34, respectively.text/plaincorona_topic_keys.txtThe top 20 words for each of 35 topics generated using the LDA algorithm fit to all tweets listed in users_ids.csvtext/plainusers_botscores.txtA tab-separated text file listing the bot scores generated from querying Botometer on March 2, 2020. The first entry is the raw (English) bot score and the second entry is the CAP score. text/plainusers_ids.csvA comma-separated file listing all tweet IDs containing coronavirus-related keywords generated by each of the 2000 accounts. The first entry on each line is a username, followed by a list of tweet IDs.text/csv