Rush Limbaugh’s been a pretty hot topic lately, and he’s certainly been a popular discussion on Social Media.
In the 24 hours preceding 8pm EDT (which is midnight, GMT), there’s been roughly 14,000 tweets that include “limbaugh” in the contents, or about 10 a minute. Keep in mind that it’s a weekend, and Rush hasn’t said anything on the air since Friday …
Sentiment
Some breakdown of the sentiment in those tweets (click on chart to enlarge):
52% of the tweets registered as weakly or strongly negative, while 21% registered as weakly or strongly positive. That’s no surprise. No matter who’s talking about Rush or their position, they’re probably not happy about what’s going on. See the comments at the end about limits of sentiment analysis.
Hash Tags
One thing that is always interesting is the use of hash tags (#winning). These are unstructured and uncontrolled, and so it is purely convention that is adopted by Twitter users. For the posts that talk about Rush, the following are the top twenty hashtags:
HashTag | Count | Percent |
#p2 | 824 | 9% |
#limbaugh | 585 | 6% |
#stoprush | 583 | 6% |
#tcot | 544 | 6% |
#boycottrush | 536 | 6% |
#gop | 262 | 3% |
#taxpayerfunded | 245 | 3% |
#flushrush | 232 | 3% |
#rush | 194 | 2% |
#snl | 186 | 2% |
#waronwomen | 182 | 2% |
#gamechange | 158 | 2% |
#cnn | 147 | 2% |
#fem2 | 126 | 1% |
#tlot | 109 | 1% |
#topprog | 107 | 1% |
#ows | 102 | 1% |
#rushlimbaugh | 94 | 1% |
#teaparty | 93 | 1% |
#news | 82 | 1% |
#p2 is the has tag for “Progressives on Twitter”. I was surprised to see it as the most popular tag. #tcot is “Top Conservatives on Twitter”. #fem2 is for feminists. #tlot is “Top Libertarians on Twitter”. What’s interesting is that there is no hashtag which is reaching critical mass. If you were to search for just #stoprush, for example, you would get only a tiny fraction of the posts about Limbaugh.
Twitter Users
There are no clear “top posters”; the most frequent poster is “Miaminonymous”, who appears to just retweet everything, with 131 posts.
The top 25 people mentioned in tweets are:
User ID | count | % of Mentions |
@thinkprogress | 480 | 4.0% |
@hipstermermaid | 320 | 2.7% |
@limbaugh | 310 | 2.6% |
@huffingtonpost | 191 | 1.6% |
@credomobile | 182 | 1.5% |
@politico | 167 | 1.4% |
@addthis | 158 | 1.3% |
@shoq | 153 | 1.3% |
@superguts | 152 | 1.3% |
@denisleary | 152 | 1.3% |
@billmaher | 133 | 1.1% |
@youtube | 131 | 1.1% |
@politicususa | 121 | 1.0% |
@tmorello | 118 | 1.0% |
@theblaze | 117 | 1.0% |
@cdibona | 114 | 1.0% |
@mediaite | 112 | 0.9% |
@anonyops | 112 | 0.9% |
@sandrafluke | 102 | 0.9% |
@thedailybeast | 95 | 0.8% |
@rushlimbaugh | 92 | 0.8% |
@krystalball1 | 80 | 0.7% |
@boingboing | 76 | 0.6% |
@stoprush | 70 | 0.6% |
@thedailyedge | 70 | 0.6% |
Interestingly, @limbaugh is not the twitter account Rush uses, @rushlimbaugh is.
Comments
What I make of this
Sentiment analysis is a mechanical assessment of the sentiment, positive or negative, in a tweet. It does not necessarily indicate approval (if positive) or disapproval (if negative) of a particular subject. Consider some contrived examples: “I hate the constant criticism of Rush” is negative, while “I am so happy that Rush is losing advertisers. I love the ones who are quitting” is very positive. The sentiment generally tells us whether the statement is happy and upbeat or negative and downbeat. In large numbers, it is a crude assessment of a topic like I am using it in this post.