Cable News Twitter Ratings for Sunday, October 27, 2013

That ol’ blackfish keeps surfacing on Twitter as another rerun of the documentary gets the most tweets overall during Sunday.

Note that all times are US Eastern Time. See notes at end for further explanations. For earlier articles on cable news twitter ratings, please see this.

Cable News Ratings for 2013-10-27

Top Shows for the day:

Category Mentions Show
Most Mentions During Hour 1653 MSNBC: Melissa Harris-Perry Show
Most Mentions During day 14002 CNN: Blackfish

Overall ratings by network

Network Tweet Count Unique Tweeters Reach Male Female
CNN 41692 27560 278058045 59 % 41 %
Fox News 18895 10041 66963083 65 % 35 %
MSNBC 15234 8471 68532958 51 % 49 %
Comedy Central 2730 2406 6357589 58 % 42 %
E 1534 1333 8191868 22 % 78 %
HBO 1129 813 2362077 65 % 35 %
HLN 565 424 2304439 39 % 61 %
FXX 36 36 253544 74 % 26 %

For networks that are not predominantly news, only news(-like) shows are included. See the detailed listings below for precise shows

 

Most popular hastags

Hashtag Count
#blackfish 14272
#lnyhbt 3919
#tcot 3886
#nerdland 2629
#uppers 2136
#thecycle 1826
#obamacare 1453
#blackfishoncnn 1353
#iran 1322
#tgdn 1135

Ratings for individual time slots

Ratings for Weekends 6am

Network Show Tweets Hour Tweets Day Male Female
CNN New Day 23 466 52% 48%
Fox News Fox and Friends Weekend 74 409 70% 30%

Ratings for Weekends 7am

Network Show Tweets Hour Tweets Day Male Female
CNN New Day (to 7:30, Sun) 20 466 52% 48%
CNN Sanjay Gupta MD (7:30 – 8) 6 181 44% 56%
E E! News Weekend 10 1534 22% 78%
Fox News Fox and Friends Weekend 46 409 70% 30%
HLN Weekend Express 0 10 25% 75%

Ratings for Weekends 8am

Network Show Tweets Hour Tweets Day Male Female
CNN New Day 24 466 52% 48%
Fox News Fox and Friends Weekend 108 409 70% 30%
HLN Weekend Express 1 10 25% 75%
MSNBC Up w/Steve Kornacki 831 2700 50% 50%

Ratings for Weekends 9am

Network Show Tweets Hour Tweets Day Male Female
CNN State of the Union w/Candy Crowley 210 561 63% 37%
Fox News Fox and Friends Weekend 102 409 70% 30%
HLN Weekend Express 0 10 25% 75%
MSNBC Up w/Steve Kornacki 919 2700 50% 50%

Ratings for Weekends 9pm

Network Show Tweets Hour Tweets Day Male Female
CNN Blackfish 151 14002 29% 71%

Ratings for Weekends 10am

Network Show Tweets Hour Tweets Day Male Female
CNN GPS w/Fareed Zakaria 65 224 70% 30%
Fox News America’s News HQ 92 207 76% 24%
HLN Weekend Express 1 10 25% 75%
MSNBC Melissa Harris-Perry Show 1653 3893 47% 53%

Ratings for Weekends 11am

Network Show Tweets Hour Tweets Day Male Female
CNN Reliable Sources 50 138 63% 37%
Fox News #MediaBuzz 129 272 73% 27%
HLN Weekend Express 2 10 25% 75%
MSNBC Melissa Harris-Perry Show 1132 3893 47% 53%

Ratings for Weekends 12pm

Network Show Tweets Hour Tweets Day Male Female
Fox News America’s News HQ 30 207 76% 24%
HLN Weekend Express 2 10 25% 75%
MSNBC Weekends w/ Alex Witt 46 114 69% 31%

Ratings for Weekends 1pm

Network Show Tweets Hour Tweets Day Male Female
Fox News America’s News HQ 38 207 76% 24%
MSNBC Weekends w/Alex Witt 35 114 69% 31%

Ratings for Weekends 2pm

Network Show Tweets Hour Tweets Day Male Female
CNN News Room 0 70 71% 29%
Fox News Fox News Sunday 167 1585 66% 34%

Ratings for Weekends 3pm

Network Show Tweets Hour Tweets Day Male Female
Fox News America’s News HQ 1 207 76% 24%
MSNBC MSNBC Live w/Craig Melvin 41 86 46% 54%

Ratings for Weekends 4pm

Network Show Tweets Hour Tweets Day Male Female
CNN News Room 35 70 71% 29%
Fox News America’s News HQ 1 207 76% 24%
MSNBC Disrupt w/ Karen Finney 328 577 48% 52%

Ratings for Weekends 5pm

Network Show Tweets Hour Tweets Day Male Female
CNN News Room 10 70 71% 29%
Fox News #MediaBuzz 23 272 73% 27%

Ratings for Weekends 6pm

Network Show Tweets Hour Tweets Day Male Female
CNN News Room 4 70 71% 29%
Fox News Fox News Sunday 104 1585 66% 34%

Ratings for Weekends 7pm

Network Show Tweets Hour Tweets Day Male Female
Fox News Fox Report Weekend 0 0 0% 0%

Ratings for Weekends 8pm

Network Show Tweets Hour Tweets Day Male Female
Fox News Huckabee 22 110 49% 51%

Ratings for Weekends 10pm

Network Show Tweets Hour Tweets Day Male Female
Fox News Stossel 67 330 72% 28%

Ratings for Weekends 11pm

Network Show Tweets Hour Tweets Day Male Female
FXX Totally Biased (Recap) 0 36 74% 26%

 


Definition of terms used in this report:

  • Network: For the purposes of total network mentions, the count is the total unique tweets that mention any of the shows tracked on the network or the network’s general Twitter account (e.g., @CNN).
  • Mentions During Hour or Tweets Hour: The number of tweets that mention the show during the hour specified. For shows that are repeat later in the day, the first (and often live) showing usually garners the most mentions by a significant margin.
  • Mentions During day or Tweets Day: The total number of mentions a show received from midnight to midnight, eastern time.
  • Tweet Count: The number of tweets (including retweets) that mention a show.
  • Unique Tweeters: The number of Twitter users who have sent one or more tweets mentioning a show. If a user sends more than one tweet, they still only count once.
  • Reach: A measure of the number of impressions a collection of tweets will make. For each tweet that is sent, it adds up how many people follow the person tweeting it — how many timelines that tweet will show up in. Thus, if network A has 10,000 mentions from people with an average of 10 followers, the reach will be 100,000. On the other hand, if network B has 10,000 mentions from people with an average of 100 followers, the reach will be 1,000,000. So network B has much greater reach: tweets mentioning network B will potentially be seen 10 times as often as tweets about network A.
  • Male / Female: An estimate of the demographics of a show’s audience. Note that this number is an imprecise estimate.

Cable News Twitter Ratings are still experimental. If you have any suggestions, find any errors, or have any questions, please feel free to contact me at admin@socialseer.com

For further discussion of how these stats are calculated, please see this blog post. Especially the part about how I determine the gender of Twitter users.