Please note that due to the current situation, participation in our on-site training events is restricted. You can find further information here.
Digital Trace Data in Social Science (Online-Workshop!)
Dr. Taehee Kim
Date: 07.12 - 08.12.2020 ics-file
Location: Online via Zoom / Course language: English
This workshop introduces Twitter API and provides multiple examples of collecting and analyzing Twitter data in R.
The course will start with general introduction of Twitter's API, available data and limitations. Subsequently, participants will learn how to collect diverse types of Twitter data (e.g., user timelines, tweets including certain keywords). To analyze collecting data, the course will discuss summary statistics of interested features, simple text analysis and network analysis (e.g. retweet network). Along with the data analysis, diverse possibilities for visualization will be demonstrated as well.
During the course, the following R packages will be used: rtweet (to collect data), tidyverse (explore and visualise data), and igraph (analyze and visualize network).
Before the course begins, participants need to apply for a developer account, which you will need to access Twitter API. You can find detailed explanation of the process at Twitter developer webpage: https://developer.twitter.com/ (Note that you need to prepare a valid Twitter account beforehand). The reviewing process usually take a couple of days, but it can take weeks. Even if you do not get approved before the workshop starts,
I can give you a temporary access that is valid during the workshop period. You need to (1) prepare a valid Twitter account and (2) let me know your @user_name of your account via e-mail before the workshop starts. Note that email notification from Twitter must be activated!
This workshop is suitable for the participants who would like to use Twitter data for their future research with R.
Participants (1) understand what kind of data can be collected from Twitter API, (2) can collect Twitter data through its API based on their own research interests, (3) can summarize and visualize the interested features of the Twitter data.
Participants should have basic knowledge about how to use R. For example, it is expected that participants are able to install libraries, read and save csv format data, handle R's basic data types and structures (e.g., list, data frame), write simple iteration (e.g., for loop) and condition (e.g., if-else) statements. It is preferable if participants have some experiences in tidyverse related packages but not necessary.