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dcc:pdpsol:dataminimization [2026/06/04 14:14] – marlondcc:pdpsol:dataminimization [2026/06/11 08:47] (current) – alba
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 === Digital traces === === Digital traces ===
-Be aware of the fact that bringing a device to an interview by itself can generate digital traces. If your phone is on, it may record GPS coordinates, connections to Wi-Fi networks, or mobile towers (depending on settings). If two phones are connected on the same tower for a period of time, this can indicate that a meeting took place. Apps or operating systems may collect data in the background (e.g. weather apps, social media or system updates). IP addresses, MAC addresses of nearby devices, or Bluetooth connections can also unintentionally reveal information about the environment or participant. All this information can later be used to determine where the interview took place and with whom. +Be aware that bringing a device to an interview can, by itself, generate digital traces. If your phone is on, it may record GPS coordinates, Wi-Fi network connections, or mobile tower signals (depending on settings). If two phones are connected to the same tower for a period of time, this can indicate that a meeting took place. Apps or operating systems may collect data in the background (e.g. weather apps, social media or system updates). IP addresses, MAC addresses of nearby devices, or Bluetooth connections can also unintentionally reveal information about the environment or participant. All this information can later be used to determine where the interview took place and with whom. 
  
-If you are plan on doing interviews with participants, and the topic is (highly) sensitive (e.g. because it is about illegal activities), then you can minimize digital traces during interviews by leaving your phone behind and using dedicated, offline recording device instead. If you must bring a phone enable airplane mode and remove the battery if possible. Consider using [[https://myuniversity.rug.nl/infonet/medewerkers/actueel/news/251107-secure-laptop-phone-travel-risk-countries?lang=nl|burner phones]] provided by the University of Groningen.+If you plan on doing interviews with participants, and the topic is (highly) sensitive (e.g. because it is about illegal activities), then you can minimize digital traces during interviews by leaving your phone behind and using a dedicated, offline recording device instead. If you must bring a phone, enable airplane mode and remove the battery if possible. Consider using [[https://myuniversity.rug.nl/infonet/medewerkers/actueel/news/251107-secure-laptop-phone-travel-risk-countries?lang=nl|burner phones]] provided by the University of Groningen.
  
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 As a researcher, you can reduce the amount of personal data you collect when conducting social media research by carefully selecting your data collection method. Here are two common research approaches, with practical tips for each: As a researcher, you can reduce the amount of personal data you collect when conducting social media research by carefully selecting your data collection method. Here are two common research approaches, with practical tips for each:
   * **Social media data scraping** is the automated collection of user-generated content and metadata from platforms like X (Formerly Twitter) and YouTube for systematic analysis. Make sure you limit the variables you collect during scraping and define clear filters to your range (e.g. keywords and date range). Consider taking a sample and not scraping all the data that falls within this range.    * **Social media data scraping** is the automated collection of user-generated content and metadata from platforms like X (Formerly Twitter) and YouTube for systematic analysis. Make sure you limit the variables you collect during scraping and define clear filters to your range (e.g. keywords and date range). Consider taking a sample and not scraping all the data that falls within this range. 
-  * **Manual data collection and observation** make it possible to carefully design your data collection and easily prevent the collection of identifiable data. You can determine what data you collect and are less dependent on API. Examples of good practices: 1) Make sure not to collect any usernames, or store them separately from the rest of your data ([[pseudonymization|pseudonymization]]). 2) [[de-identification|De-identify]] other personal identifiable information that is not necessary for your research purpose during data collection.  +  * **Manual data collection and observation** make it possible to carefully design your data collection and easily prevent the collection of identifiable data. You can determine what data you collect and are less dependent on API. Examples of good practices: 1) Make sure not to collect any usernames or store them separately from the rest of your data ([[pseudonymization|pseudonymization]]). 2) [[de-identification|De-identify]] other personal identifiable information that is not necessary for your research purpose during data collection.