Project Report: Political Propaganda & Social Media

All seeing eye illustration

In 2019 Ellen Lechman and I embarked on a research project to begin assessing the use of social media to spread propaganda in nations other than the United States. With this focus in mind, we conducted a literature review of recent research on propagandistic interventions occurring in Asian and European nations. We surveyed available academic and other institutional publications, and produced an annotated bibliography detailing a baker's dozen of sources we deemed most relevant.

Annotation: When search engines stopped being human: menu interfaces and the rise of the ideological nature of algorithmic search

Carol Kuhlthau’s Information Search Process with Google Search superimposed

In recent years, some have argued that if you can’t find information on Google, it might as well not exist. This assertion is problematic given that according to various estimates, the scope of Google’s search index range from 4 percent to .004 percent of the total Internet. Neils Kerssens examines these questions in the context of “positivist algorithmic ideology,” a normalizing force that frames certain practices as an established standard exempt from further interrogation.

Annotated Bibliography: How Humanities Scholars Find, Access, and Use Audiovisual Archives in Research

abstract poster about finding things

I recently completed a short annotated bibliography during a research project for Information Science 501 at the University of Illinois iSchool. I'm interested in the information seeking behavior of academic researchers in relation to resources in audiovisual archival collections, so as to better understand how the materials might be made more findable and useable by humanities scholars. I assumed I would find a wide range of research on this topic. I was wrong.

Annotation – A Bundle of Open Source Resources for Social Media Data Mining and Analysis

command line graphic of hand tools

We've reached the final annotation in our series on "Social Media Data Collection, Processing, and Use in Research, Marketing, and Political Communication." Toward the end of the project my research drifted from traditional academic sources to investigative journalism. We now veer further off-track into blog posts and GitHub repos. Some videos and a course syllabus on Data Science for Social Systems. Tools, documentation, and related sources that don't fit neatly into any particular box. This isn't so much an annotation as a grab bag of annotated links. I apologize in advance.

Annotation – Cambridge Analytica: Undercover Secrets of Trump’s Data Firm

Cambridge Analytica staff saying it's no good winning an election on the facts

In the third and final part of their undercover investigation, Channel 4 News captures chief executives from Cambridge Analytica explaining how the firm used social media analytics to win the 2016 U.S. presidential election for Donald Trump. After this report was aired in March, Cambridge Analytica executives denied using social media analytics to win the election for Donald Trump. In earlier parts of this report, they claim to always tell the truth, while adding that actually people may not know or care what's true and what isn't. Anyway if people were misled it's not their fault. Also, these are not the 'driods you're looking for.

Annotation – Cambridge Analytica Uncovered: Secret filming reveals election tricks

Screenshot of video Cambridge Analytica Uncovered

The Cambridge Analytica story is what inspired me to pursue research on the details and methods of data processing that form the technical basis of using social media metadata for psychographic purposes, and the role of programming in accessing, collecting, processing, and using social media data, and the specific tools and workflow that enable this work. But I believe we can't fully understand the technical story without the political and social context. Technology isn't neutral, and our values are embedded in every tool we build. London's Channel 4 News discovered the values held by senior executives of Cambridge Analytica, as they detail in part two of their investigative report.

Annotation – Channel 4 News Report – Cambridge Analytica: Whistleblower reveals data grab of 50 million Facebook profiles

So far in this project I've been annotating traditional academic sources. These sources explore methods of machine learning, Natural Language Processing, sentiment analysis, and the tools used to mine social media for research purposes. But the literature hasn't kept pace with the news, and social media data is being used for things other than academic research. Like maybe stealing elections. Here begins a series of three annotations of investigative reports by London's Channel 4 News. These are video stories about Cambridge Analytica and its methods and role in political campaigns in the U.S., Africa, Europe and beyond. These are of course non-traditional annotations. But I consider the source credible, and given the subject important to include.

Annotation – Technology Firms Shape Political Communication: The Work of Microsoft, Facebook, Twitter, and Google With Campaigns During the 2016 U.S. Presidential Cycle

megaphone shouting social media icons

If you ran digital strategy for a presidential campaign, and Facebook came knocking on your door and said "We want to help you win this election," would you turn them down? There's nothing like a little help from the mothership.

Annotation: A 61-Million-Person Experiment in Social Influence and Political Mobilization

Sign saying spread the vote

Finally, a break from annotating technical stuff. Don't get me wrong I like it but...here's where it hits the road: Changes in voting behavior. Here we have a study published in 2012 in Nature on a randomized controlled study of changes in users voting behavior after seeing different versions of messages on Facebook. You want to read this one.

Annotation – Social Media Analysis – Challenges in Topic Discovery, Data Collection, and Data Preparation

Today's annotation summarizes an article published in late 2017 reporting on a systematic literature review of existing research on social media analytics. The authors seek to identify challenges that have not yet been solved by the models or the tools. I'll give you a hint at what they find: We are very good at looking for specific needles in the social media haystack, but not so good at finding the needles we're not looking for.
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