Nielsen released an
independent Twitter Causation study today that proves Twitter activity influences Live TV Ratings, while Live TV Ratings simultaneously impact program-related Tweet volume.
The study set out to discover if Tweets were driving TV Ratings, or if TV Ratings increased Twitter activity around shows already being watched. According to the research findings, while one hand does appear to feed the other, it’s more frequent that Live TV Ratings increase Twitter activity around TV programming, versus Tweet volume increasing Live TV ratings.
Of the 221 broadcast primetime program episodes analyzed for the study, Live TV Ratings significantly impacted program-related Tweets for 48 percent of the episodes. At the same time, the volume of program-related Tweets resulted in “statistically significant changes” for Live TV Ratings with 29 percent of the episodes.
“Using time series analysis, we saw a statistically significant casual influence indicating that a spike in TV ratings can increase the volume of tweets, and, conversely, a spike in tweets can increase tune-in,” said Nielsen chief research officer Paul Donato.
“These results substantiate what many of our TV partners have been telling us anecdotally for years: namely, that Twitter drives tune-in, especially for live, linear television programming,” said Twitter COO Ali Rowghani.
Beyond the relationship between Twitter and TV Ratings, the study examined how Twitter activity affected TV ratings by program genre:
Tweets had the greatest impact on programs in the competitive reality genre, influencing ratings changes in nearly half (44 percent) of episodes. Episodes in the comedy (37%) and sports (28%) genres also saw significant increased tune-in from tweets, while programs in the drama genre were less affected (18%) by tweets during episodes.
To conduct the study, Nielsen analyzed minute-to-minute trends, and used a time series analysis methodology developed by Nobel Prize winning economist Clive Granger. Nielsen claims this is the first study that quantifies the effects of Twitter on tune-in rates for television programming.
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