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Surveillance Using Facial Recognition and Social Media Data
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
2019 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

People share more and more on social media, aware that they are being surveilled but unaware of the scope and the ways that their data is processed. Large amounts of resources are dedicated to performing the surveillance, both in terms of labor and computation. This project explores the scope of data collection and processing by showing that it is possible to gather, process, and store data from the social media platforms Twitter and Reddit in real-time using only a personal computer. The focus was to use facial recognition to find specific individuals in the stream of data, but the data collected can be used for other purposes. We have also explored the ethical concerns regarding both the collection and processing of such data.

Abstract [sv]

Människor delar mer och mer på social medier medvetna om att de blir övervakade, men omedvetna om i vilken utsträckning och på vilka sätt datan är processad. Idag används mycket resurser för att urföra dessa uppgifter. Med det här projektet visar vi att det är möjligt att samla in, processa och spara data från sociala medierna Reddit och Twitter i realtid genom att enbart använda en persondator. Vårat fokus har varit att använda ansiktsigenkänning för att identifiera specifika individer från en dataström, men datan kan användas för andra syften. Vi har också kollat på de etiska dilemman som dyker upp i samband med insamling och processning av sådan data.

Place, publisher, year, edition, pages
2019. , p. 22
Series
Independent Project in Computer and Information Engineering ; 2019-003
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:uu:diva-385696OAI: oai:DiVA.org:uu-385696DiVA, id: diva2:1325392
External cooperation
Aleksander Okonski
Educational program
Master of Science Programme in Information Technology Engineering
Supervisors
Examiners
Available from: 2019-06-20 Created: 2019-06-15 Last updated: 2019-06-20Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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More languages
Output format
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