Projections of Power: Framing News, Public Opinion, and U.S. Foreign Policy

Too Much to Know. Managing Scholarly Information before the Modern Age

All data have biographies: they are collected, cleaned, and complied before they could support powerful decisions. Every junction on this trajectory matters. Yet, according to Catherine D’Ignazio a...

Data feminism: by Catherine D’Ignazio and Lauren F. Klein, Cambridge, MA, The MIT Press, 2020, pp. 328, hardcover $29.95, ISBN 9780262044004

In online communities, antisocial behavior such as trolling disrupts constructive discussion. While prior work suggests that trolling behavior is confined to a vocal and antisocial minority, we demonstrate that ordinary people can engage in such behavior as well. We propose two primary trigger mechanisms: the individual's mood, and the surrounding context of a discussion (e.g., exposure to prior trolling behavior). Through an experiment simulating an online discussion, we find that both negative mood and seeing troll posts by others significantly increases the probability of a user trolling, and together double this probability. To support and extend these results, we study how these same mechanisms play out in the wild via a data-driven, longitudinal analysis of a large online news discussion community. This analysis reveals temporal mood effects, and explores long range patterns of repeated exposure to trolling. A predictive model of trolling behavior shows that mood and discussion context together can explain trolling behavior better than an individual's history of trolling. These results combine to suggest that ordinary people can, under the right circumstances, behave like trolls.

/pdf/anyone-can-become-a-troll-causes-of-trolling-behavior-in-1ojxvpz3eq.pdf

Anyone Can Become a Troll: Causes of Trolling Behavior in Online Discussions

Cutting-edge data science techniques can shed new light on fundamental questions in educational research. We apply techniques from natural language processing (lexicons, word embeddings, topic mode...

/pdf/content-analysis-of-textbooks-via-natural-language-d31ng41cza.pdf

Content Analysis of Textbooks via Natural Language Processing: Findings on Gender, Race, and Ethnicity in Texas U.S. History Textbooks:

In this article we describe our experiences with computational text analysis involving rich social and cultural concepts. We hope to achieve three primary goals. First, we aim to shed light on thorny issues not always at the forefront of discussions about computational text analysis methods. Second, we hope to provide a set of key questions that can guide work in this area. Our guidance is based on our own experiences and is therefore inherently imperfect. Still, given our diversity of disciplinary backgrounds and research practices, we hope to capture a range of ideas and identify commonalities that resonate for many. This leads to our final goal: to help promote interdisciplinary collaborations. Interdisciplinary insights and partnerships are essential for realizing the full potential of any computational text analysis involving social and cultural concepts, and the more we bridge these divides, the more fruitful we believe our work will be.

/pdf/how-we-do-things-with-words-analyzing-text-as-social-and-4hyjibmm58.pdf

How We Do Things With Words: Analyzing Text as Social and Cultural Data.

In this article we describe our experiences with computational text analysis. We hope to achieve three primary goals. First, we aim to shed light on thorny issues not always at the forefront of discussions about computational text analysis methods. Second, we hope to provide a set of best practices for working with thick social and cultural concepts. Our guidance is based on our own experiences and is therefore inherently imperfect. Still, given our diversity of disciplinary backgrounds and research practices, we hope to capture a range of ideas and identify commonalities that will resonate for many. And this leads to our final goal: to help promote interdisciplinary collaborations. Interdisciplinary insights and partnerships are essential for realizing the full potential of any computational text analysis that involves social and cultural concepts, and the more we are able to bridge these divides, the more fruitful we believe our work will be.

/pdf/how-we-do-things-with-words-analyzing-text-as-social-and-4jurn6pxoj.pdf

How we do things with words: Analyzing text as social and cultural data

Contemporary approaches to the investigation of digital resources are dominated by the paradigm of free-form natural language search, popularised by Google. The Google form of searching has shaped ...

/pdf/negotiating-the-born-digital-a-problem-of-search-2p121w5qmb.pdf

Negotiating the born-digital: a problem of search

This article considers how the development, promotion and adoption of a set of core values for web archives, linked to principles of “good governance”, will help them to tackle the challenges of sustainability, accountability and inclusiveness that are central to their long-term societal and cultural worth. It outlines the work that has already been done to address these questions, as web archiving begins to move out of its establishment phase, and then discusses seven key principles of good governance that might be adapted by and embedded within web archives: participation, consensus, accountability, transparency, effectiveness and efficiency, inclusivity and legality. The article concludes with a call to action for researchers and archivists to co-create the core values for web archives that will be required if they are to remain a vital part of our cultural heritage infrastructure.

/pdf/the-values-of-web-archives-1iy29gfa3m.pdf

The values of web archives

/pdf/big-uk-domain-data-for-the-arts-and-humanities-2pwu8w95w9.pdf

Big UK Domain Data for the Arts and Humanities

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