The Sochiatrist Social Data Extractor consists of a series of programs that allow you to get
an individual's private and public social media data, and store it in an easy to analyze CSV format.
Note: This software only works on Macs and macOS based operating systems.
Make sure that you've downloaded the linked zip file above, and that you've extracted it to a folder entitled Sochiatrist on your Desktop. Inside this folder, there should be a folder entitled sochiatrist-social-data-extractor.
The program will automatically install the requirements that are needed. Enter your computer password when the program prompts you for it. It will then ask you a series of questions about what kind of data you would like to extract from the participant (what kind of phone, what kinds of social media data), and will generate corresponding individual CSV files for each social media type.
python ~/Desktop/Sochiatrist/sochiatrist-social-data-extractor/timeanonymizer.py [name of output file]
Make sure to replace [name of output file] with the name that you'd like for the output CSV file (for example, July25th-August10th-Participant20). This program will make a file with all of the messages from your selected date range, in order based on when the messages were sent. If you have multiple date ranges you need data from, just repeat this step. The program will also run the anonymizer script if you want to anonymize the messages.
If you have extracted Facebook data, the anonymization script will use the Facebook friends list to anonymize names within each message (e.g., "Jeff and I went to the mall" would become "038d017c and I went to the mall". If you have not extracted Facebook data, the sender and the reciever of the message will be anonymized, but not names within messages.
Delete all participant data. This might include the iPhone backup, the zip file and folder of Facebook data (which will be in your Downloads folder), and the unanonymized CSVs from each individual social media type in your CSVs folder. After you've cleaned up all unneeded participant data, you're done!
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After completing the data extraction process, you can expect to find all messages in a CSV entitled anonymized_[name of participant].csv. The data will look like this.
As you can see above, all numbers are replaced with a pound sign/hashtag, all names are replaced with hashed representations of the name (e.g., 7ac988b056981), and all conversation participants are also anonymized in the fourth column.