Uncovering social semantics from textual traces: A theory‐driven approach and evidence from public statements ofU.S.Members ofCongress

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.

A Frame of Mind: Using Statistical Models for Detection of Framing and Agenda Setting Campaigns

“…Manually looking at some sampled n-grams it appears that mid-length n-grams are shared "talking points" and longer n-grams are full citations from bill proposals and committee reports. These findings are in line with textual sharing semantics (Lin et al, 2015).…”

Considering Network Effects in the Design and Analysis of Field Experiments on State Legislatures

“…For interference dynamics that do not require exposure through the network, but require uptake, researchers should look for networks that signal ideological similarity such as co-voting on bills. However, some interference dynamics for which uptake might be highly likely, such as reuse of issue framing in legislators’ public statements (Lin, Margolin, and Lazer 2016), or the adoption of strategies in responding to constituent requests (Grose, Malhotra, and Parks Van Houweling 2015), would require legislators to be exposed to each other through explicit communication channels. In applications where the network needs to play an important role in signaling exposure, networks such as Twitter-follower networks and caucus comembership may be more appropriate.…”

Semantic Networks and Applications in Public Opinion Research

“…A recent study shows that using n-grams of different size might reveal different causal mechanisms that lead to similarity in statements produced by US Congressman. While addressing similar topics (i.e., topic similarity) was positively correlated with authors' patterns of using similar words and phrases only when the raw corpus was preprocessed with shorter n-grams (n < 3), working in the same chamber was positively correlated with author-author similarity in language use when longer n-grams were incorporated as tokens (n > 16) (Lin, Margolin, and Lazer, 2015). This suggests that independently constructing messages is likely to pose a limit on the length of phrases used, but directly copying others' statements poses no such restraint.…”