United Kingdom

This article introduces a dataset of all posts by candidates during the 2024 General Election in the United Kingdom with a presence on the X (formerly Twitter) platform. The article relies on a crowd-sourcing innovation in the United Kingdom that, for the first time, provided researchers with early access to a regularly updated candidate list prior to the start of the election. This made it possible to collect real-time data on candidate posts for 1,604 candidates across 53 separate political parties. Additionally, we download and store 53,327 images and 15,982 videos posted within tweets. We enrich the data with the realized vote count and vote share for each candidate as well as text transcripts extracted from the audio of video posts. Overall, the dataset provides a uniquely comprehensive collection of online campaigning material for an election campaign and will be of considerable value to scholars of political communication, elections, and democratic responsiveness. We also analyze the topics and tone — focusing on negativity — across different media formats to identify patterns in the content and style of candidate communication across parties.

This paper uses geolocated Twitter histories from approximately 25,000 individuals in 6 different time zones and 3 different countries to construct a proper time-zone dependent hourly baseline for social media activity studies.  We establish that, across multiple regions and time periods, interaction with social media is strongly conditioned by traditional bio-rhythmic or “Circadian” patterns, and that in the United States, this pattern is itself further conditioned by the ideological bent of the user. Using a time series of these histories around the 2016 U.S. Presidential election, we show that external events of great significance can disrupt traditional social media activity patterns, and that this disruption can be significant (in some cases doubling the amplitude and shifting the phase of activity up to an hour). We find that the disruption of use patterns can last an extended period of time, and in many cases, aspects of this disruption would not be detected without a circadian baseline.