Partisan Political Talk Show Audiences Similar in Their Differences

Political talk shows have helped to create and perpetuate the massive divide between American liberals and conservatives.  To better understand how polarized these audiences really are, we used Canvs, our proprietary analytics tool, to analyze four programs: the conservative-leaning The O'Reilly Factor and Hannity onFox News, and the liberal-leaning The Rachel Maddow Show and All in with Chris Hayes on MSNBC. In our analysis, we investigated the similarities and differences between these audiences’ emotionally-charged reactions on Twitter. We captured conversation on daily episodes of these shows airing from August 18 - August 20, 2014.*

Though there are stark ideological differences between conservatives and liberals, reactions among viewers mirrored each other on both sides of the political spectrum. Emotions in both groups were dominated by eerily similar extremes: reverence and disdain. The real driver of unique emotions for each show was not ideology, but each host’s defining personal attributes.

*Bill O’Reilly only appeared on his August 20th show - Eric Bolling hosted The O’Reilly Factor on August 18-19.

Admiration and Hate-Watching Are The Norm

Despite the dark nature of most of the leading stories in this week’s news, love and respect for the hosts drove the greatest percentage of conversation across all four shows. At the same time, however, audiences were extremely frustrated with political figures and news stories, and they directed a great deal of this animosity towards the hosts they disagreed with. Perhaps more interestingly, people hate-watched all four shows, regardless of ideology.

Reactions to Political Talk Show Hosts

Conservative-Leaning Programs

Posts during The O’Reilly Factor mentioning the host's Twitter handle (@OReillyFactor) were driven by “love” reactions,which made up 28% of related emotional conversation. Bill O’Reilly supporters generally commented on how they agreed with his message and opinion.

Among discussion containing @OReillyFactor, 4% fell into the “idiot” category, a rare category for Canvs. Many of the comments expressed general negativity toward O'Reilly, while some explicitly mentioned disappointment with the host's coverage of events in Ferguson.

Within mentions of Sean Hannity’s Twitter handle (@SeanHannity) during Hannity, 24% of posts fell into the “love” category. Most “love” posts complimented Hannity’s interviews as being informative and interesting to watch.

Similar to O’Reilly, 6% of conversation containing @SeanHannity referred to the host as an “idiot." These comments generally referred to the way Hannity approached controversial issues.

Liberal-Leaning Programs

Of all reactions during The Rachel Maddow Show containing her Twitter handle (@Maddow), 33% expressed “love,” which was the most popular category. Maddow supporters often cited her professionalism and directness, while others simply complimented her coverage more generally.

At the same time, 19% of reactions to @Maddow during Maddow’s show fell into the “hate” category. Some of this conversation referred to dismay about the situation in Ferguson, but the vast majority consisted of negativity towards Maddow herself.

“Love” was the largest bucket of conversation during All In With Chris Hayes that mentioned @ChrisLHayes, which was represented in 40% of reactions. These reactions generally complimented his reporting.

Conversely, 3% of conversation mentioning @ChrisLHayes during the show expressed that he was an “idiot." A significant portion of discussion in this category was driven by one particularly incendiary tweet, which was retweeted 23 times.

Political talk shows evoke extreme, yet similar, reactions on both sides of the aisle. People primarily watch political talk shows because they love the host and the host’s coverage of major news events. At the same time, people also watch political talk shows that conflict with their own political views to take their frustration out on the hosts. Both of these trends hold true regardless of political leanings.

Differentiation Stems From Host Style, Not Ideology

Based on our analysis of these four shows, most people watch certain political talk shows to affirm their own ideology. This is why different audiences experience the same emotions, but in response to different content. However, we found that the emotions that were unique to each show did not occur in response to the host’s ideology, but rather due to his or her particular strengths.

Talk Show Host Style Breakdown

O’Reilly: The “funniest.” Within @OReillyFactor conversation, 5% said they were “laughing” during the show. While some of the conversation was driven by people laughing at the show's premise, many posts were laughing with O’Reilly. The following tweet, which captures a quote from a guest on The O’Reilly Factor was retweeted 67 times.

Hannity: The most “strongly anticipated.” Within @SeanHannity conversation, 9% said they “look forward” to some aspect of his show. People were generally excited to see Hannity’s interviews.

Maddow: The most “intelligent.” Within @Maddow conversation, 6% of posts described her as “intelligent." Discussion in this category generally focused on her understanding of major issues.

Hayes: The most “impressive.” Within @ChrisLHayes conversation, 4% said they were “impressed” with him. Many posts focused on his ability to communicate complicated ideas.

Most people have similar motivations for choosing to watch political talk shows, namely to reinforce existing political views, but they also frequently express affinity for the host's personality. This analysis underscores the idea that conservatives and liberals have more in common than is readily apparent: both sides are equally excited and frustrated when it comes to politics. In an intense and polarizing political climate where people are often separated by ideology before engaging in discourse, it is interesting to see that everyone is experiencing similar emotions while learning about important political issues.

Graphics and additional reporting by Mattan Ingram. 

Tweet Source: Nielsen. Relevant Tweets captured from three hours before, during, and three hours after an episode’s initial broadcast, local time