Lin, YR and Margolin, D and Lazer, D
(2016)
Uncovering social semantics from textual traces: A theory-driven approach and evidence from public statements of U.S. Members of Congress.
Journal of the Association for Information Science and Technology, 67 (9).
2072 - 2089.
ISSN 2330-1635
![[img]](http://d-scholarship.pitt.edu/style/images/fileicons/text_plain.png) |
Plain Text (licence)
Available under License : See the attached license file.
Download (1kB)
|
Abstract
The increasing abundance of digital textual archives provides an opportunity for understanding human social systems. Yet the literature has not adequately considered the disparate social processes by which texts are produced. Drawing on communication theory, we identify three common processes by which documents might be detectably similar in their textual features—authors sharing subject matter, sharing goals, and sharing sources. We hypothesize that these processes produce distinct, detectable relationships between authors in different kinds of textual overlap. We develop a novel n-gram extraction technique to capture such signatures based on n-grams of different lengths. We test the hypothesis on a corpus where the author attributes are observable: the public statements of the members of the U.S. Congress. This article presents the first empirical finding that shows different social relationships are detectable through the structure of overlapping textual features. Our study has important implications for designing text modeling techniques to make sense of social phenomena from aggregate digital traces.
Share
| Citation/Export: |
|
| Social Networking: |
|
Details
Metrics
Monthly Views for the past 3 years
Plum Analytics
Altmetric.com
Actions (login required)
 |
View Item |
![[feed]](/images/feed-icon-32x32.png){kind=icon}