Data portraits : aesthetics and algorithms
Name
608305541-MIT.pdf
Description
Full printable version
Size
14.55 MB
Format
Adobe PDF
Checksum (MD5)
dd7a8c84c05719f1da4997f0e65cc425
Author(s)
Dragulescu, Alexandru C
Advisor(s)
Judith Donath.
Date Issued
2009
Publisher
Massachusetts Institute of Technology
Abstract
While interacting online, one generates a multitude of personal data trails, both textual and behavioral. The data portrait is a way to collect, condense and represent these information trails, which are often time consuming and tedious to find and grasp when read linearly across web pages or domains, into an easy, legible, and compelling visualization. This thesis presents various data portraiture techniques that generate both individual and collective portraits of users participating in online social media. The data used in generating the portraits are unstructured text and publishing timestamps of Twitter micro-blog posts, as well as aggregate RSS feeds from FriendFeed. The strategies for depicting people's online personas explored in this thesis focus on the compression, mapping and visual representation components of the visualization pipeline. The resulting portraits attempt to maintain a tight connection with the data, and be legible to viewers, but at the same time, venture to explore more expressive visual forms, and engage with the evolving aesthetics of cinematography, typography and animation.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2009.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 91-93).
Subjects
Architecture. Program in Media Arts and Sciences.
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
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copyright. They may be viewed from this source for any purpose, but
reproduction or distribution in any format is prohibited without written
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