Social Media, News and Political Information during the US Election: Was Polarizing Content Concentrated in Swing States? (1802.03573v1)

Abstract: US voters shared large volumes of polarizing political news and information in the form of links to content from Russian, WikiLeaks and junk news sources. Was this low quality political information distributed evenly around the country, or concentrated in swing states and particular parts of the country? In this data memo we apply a tested dictionary of sources about political news and information being shared over Twitter over a ten day period around the 2016 Presidential Election. Using self-reported location information, we place a third of users by state and create a simple index for the distribution of polarizing content around the country. We find that (1) nationally, Twitter users got more misinformation, polarizing and conspiratorial content than professionally produced news. (2) Users in some states, however, shared more polarizing political news and information than users in other states. (3) Average levels of misinformation were higher in swing states than in uncontested states, even when weighted for the relative size of the user population in each state. We conclude with some observations about the impact of strategically disseminated polarizing information on public life.

• The paper investigates whether polarizing political content on social media was disproportionately concentrated in swing states during the 2016 US Presidential Election.
• Researchers analyzed millions of tweets with geolocation data around the election period, categorizing linked URLs to identify the prevalence and source types of political information shared.
• Key findings reveal that swing states exhibited a higher concentration of misinformation and polarizing content compared to non-contested states, suggesting potential targeted dissemination influencing voter behavior.

Analysis of Polarizing Social Media Content During the 2016 US Election

The dissemination of polarizing political content during the critical period surrounding the 2016 United States Presidential Election has been a focal point for researchers studying the influence of social media on public discourse. In the data memo "Social Media, News and Political Information during the US Election: Was Polarizing Content Concentrated in Swing States?" by Philip N. Howard et al., an investigation is conducted to evaluate whether this contentious content was disproportionately concentrated in swing states as opposed to being evenly distributed across the country.

Methodology and Data Collection

The researchers utilized a collection of 22,117,221 tweets curated from Twitter's Streaming API during a ten-day period around the election, focusing on political hashtags. A subset of these tweets, amounting to approximately 7,083,691, was identified based on self-reported geolocation information to determine their state of origin. Out of this subset, 1,275,430 tweets were analyzed further as they contained URLs linking to various news sources. These URLs were categorized into multiple types, such as major and minor news brands, government and expert content, and polarizing and conspiracy content, which included Junk News, WikiLeaks, and Russian sources.

Key Findings

The analysis reveals several pertinent findings:

1. Prevalence of Misinformation: Nationally, Twitter users were exposed to higher volumes of misinformation and polarizing content than professionally produced news. This pattern was notably present across the board but particularly concentrated in swing states.
2. Concentration in Swing States: Swing states exhibited a higher average level of misinformation compared to non-contested states. This was calculated through an index ratio measuring the share of junk news to overall political content shared in each state. Notably, swing states such as Florida, Pennsylvania, and Virginia had disproportionately high concentrations of such content.
3. Content Source Disparities: Among the links shared, only 20% originated from professional news organizations, whereas a greater proportion linked to polarizing and conspiracy content. The dominance of these content types underscores the deliberate use of sensationalistic and ideologically charged materials intended to influence voter perceptions and behavior.

Implications and Speculations

This paper provides empirical evidence indicative of how social media can actively shape the information ecosystem during pivotal political moments. The finding that swing states received higher doses of polarizing content suggests that targeted dissemination strategies during elections could potentially sway electoral outcomes, raising concerns over electoral integrity and the role of computational propaganda.

From a theoretical perspective, the paper accentuates the power of social media platforms as vessels for both legitimate information dissemination and political manipulation. Practically, it urges a re-evaluation of how these platforms are monitored and regulated, especially in periods leading up to significant electoral events.

Looking forward, the paper suggests avenues for further research into the evolving dynamics of misinformation campaigns and their operational mechanics across different social media platforms. Continued exploration into algorithmic biases and bot interventions could illuminate paths to mitigate the spread of misleading content. Overall, this research stands as a pivotal contribution to understanding the intersection of technology, political communication, and electoral processes.