Monday, September 28, 2015

NWS Office Facebook and Twitter Update

Every six months or so I take a look at the social media presence of the 118 National Weather Service forecast office (not including San Juan, Guam, and American Samoa). The previous analysis of both the Facebook and Twitter followers is located here ( http://us-climate.blogspot.com/2015/03/nws-social.html ). Please note that the three Alaska NWS Office share a single Facebook page, yet have separate Twitter pages. In lieu of a complete replication of the March 28th post, I want to show a snapshot of where things stand as of now.

A note of caution. While rankings are labeled on the maps, and while it is human nature to make comparisons, keep in mind that the needs and demographics of each WFO are different.

Facebook:

The three Facebook maps below show the raw number of Likes (Figure 1), the rate of Likes per 100,000 population (Figure 2), and the change in Likes over the last six months (Figure 3).

Figure 1. Facebook Likes for 118 National Weather Service forecast offices as of September 28, 2015. Rank label (highest to lowest) added to each WFO.


Figure 2. Facebook Likes per 100,000 population for 118 National Weather Service forecast offices as of September 28, 2015. Rank label (highest to lowest) added to each WFO.


Figure 3. Rate of change of Facebook Likes for 118 National Weather Service between March 28, 2015, and September 28, 2015. Percent change labelled for each WFO.


Twitter

Twitter functions quite a bit differently than Facebook. While Facebook is a more casual source of information, Twitter is much more like a news aggregation site. The information is short, sweet, and timely. My experience has been that Twitter is much more of a specialized type of social media where the participants are in the media, celebrities, actors, athletes, and subject matter specialists.

So, here are my two maps for Twitter. The first (Figure 4, shows the number of Twitter followers for each NWS page. The second show the average number of Tweets sent out by those offices since their Twitter account was activated (Figure 5).

Figure 4. Twitter followers for 120 National Weather Service forecast offices as of September 28, 2015. Rank label (highest to lowest) added to each WFO. (Alaska offices separated out).

Figure 5. Twitter followers per 100,000 population for 120 National Weather Service forecast offices as of September 28, 2015. Rank label (highest to lowest) added to each WFO. (Alaska offices separated out).

Figure 6. Number of Tweets per month sent by the 118 National Weather Service forecast offices as of September 28, 2015. Rank label (highest to lowest) added to each WFO. Value computed by dividing number of tweets by number of months since page's inception. (Alaska offices combined).


Table 1. Raw count of Facebook Likes, Twitter Followers, Tweets, and rate of Tweets by National Weather Service Forecast Office (WFO). Separate entries made for the Alaska WFOs so that Twitter statistics are identifiable. They share identical Facebook values.

WFOFB LikesTwitter FollowersTotal TweetsTweets / Month
Aberdeen9,4633,4252,28558.0
Albany28,4815,7895,438141.6
Albuquerque9,1655,27911,200258.3
Amarillo39,2887,7923,984101.2
Anchorage43,699*4,9512,50165.8
Austin/San Antonio16,33610,3008,812218.1
Baltimore/Washington38,99210,7004,705133.0
Billings14,1863,4644,207104.1
Binghamton85,1977,2839,264254.8
Birmingham78,00917,10012,000297.0
Bismarck20,5923,3124,601113.9
Blacksburg22,6075,7858,358223.6
Boise15,1073,9182,75277.8
Boston72,27532,70017,200447.9
Brownsville23,8984,1476,063150.1
Buffalo10,6947,8411,90056.9
Burlington20,5035,8276,228162.2
Caribou28,6682,4218,889274.8
Charleston (SC)8,40110,2009,228176.0
Charleston (WV)29,9445,1181,87147.5
Cheyenne11,7192,9244,455113.1
Chicago112,55620,80011,400296.9
Cleveland15,6795,9542,65567.4
Columbia12,2923,8485,199109.7
Corpus Christi10,1884,5353,76393.1
Dallas/Fort Worth102,44139,00012,800316.8
Davenport/Quad Cities13,3804,8163,28983.5
Denver/Boulder16,61511,4006,047153.5
Des Moines29,7789,9797,981202.6
Detroit/Pontiac12,2596,0263,27383.1
Dodge City9,8204,2916,904170.9
Duluth8,8382,2042,59475.5
El Paso5,9714,3179,264213.6
Elko6,9432,2857,386182.8
Eureka11,5493,0515,909146.2
Fairbanks43,699*2,6001,96751.8
Flagstaff11,6606,2864,175103.3
Gaylord9,8222,8089,675245.6
Glasgow10,5382,5072,09751.9
Goodland7,5093,4466,866174.3
Grand Forks10,0753,1243,33484.6
Grand Junction5,6312,2495,073143.4
Grand Rapids19,7105,5503,77295.8
Gray/Portland13,0484,6796,611172.2
Great Falls7,9133,4589,199227.7
Green Bay8,3923,9162,40959.6
Greenville-Spartanburg15,6024,9955,253133.4
Hastings19,2104,3657,453189.2
Honolulu17,2488,0501,72232.8
Houston/Galveston18,02411,4006,037153.3
Huntsville27,61910,9004,687116.0
Indianapolis20,74714,9008,245209.3
Jackson (KY)12,7603,8557,853199.4
Jackson (MS)75,29513,20014,400356.4
Jacksonville8,4564,0524,787118.5
Juneau43,699*2,1097,627200.7
Kansas City/Pleasant Hill82,30224,1009,481180.8
Key West28,0817,8634,226104.6
La Crosse12,2704,0066,022152.9
Lake Charles11,1153,3385,264130.3
Las Vegas10,5938,8449,026223.4
Lincoln30,9486,6474,746120.5
Los Angeles/Oxnard18,94515,8008,195208.1
Louisville21,3728,8688,821224.0
Lubbock8,1555,6805,272130.5
Marquette16,7434,0033,72292.1
Medford12,4302,7391,42735.3
Melbourne13,3145,0864,148102.7
Memphis22,4139,8209,628238.3
Miami15,06913,3008,395207.8
Midland/Odessa12,8363,4168,470209.6
Milwaukee/Sullivan25,6525,1694,797121.8
Minneapolis/Twin Cities23,45515,40010,300261.5
Missoula8,7573,5869,657239.0
Mobile/Pensacola25,05214,40012,200301.9
Morristown/Knoxville18,6153,8743,19879.1
Mount Holly/Philadelphia67,48217,3002,63767.0
Nashville55,70713,60014,200360.5
New Orleans/Baton Rouge32,0687,5876,010148.7
New York46,26824,6008,252209.5
Newport/Morehead City12,5052,9415,538152.3
Norman/Oklahoma City173,83953,00014,200390.5
North Little Rock64,21519,1002,86170.8
North Platte7,6583,6777,308185.5
Northern Indiana40,18010,10011,200284.4
Omaha/Valley13,2838,7784,701119.4
Paducah44,80710,1008,107205.8
Peachtree City/Atlanta26,78210,3004,377108.3
Pendleton9,2012,4612,05252.1
Phoenix10,56710,5006,978172.7
Pittsburgh48,43313,5005,404144.6
Pocatello4,0142,4659,095225.1
Portland19,6336,8935,465142.3
Pueblo5,9393,8055,377133.1
Raleigh12,5457,8733,47192.9
Rapid City11,5193,4521,30633.2
Reno14,6574,8335,024124.3
Riverton10,8412,0047,613193.3
Sacramento18,59910,20011,900302.1
Salt Lake City8,05210,20010,400257.4
San Angelo16,3364,6365,234129.5
San Diego13,4276,35512,500288.3
San Francisco Bay Area/Monterey18,98917,10016,800426.5
San Joaquin Valley/Hanford14,7394,20411,500284.6
Seattle12,8397,6702,81273.2
Shreveport29,5334,06911,500292.0
Sioux Falls21,46410,3007,619188.6
Spokane12,3184,6185,67370.6
Springfield27,2608,9644,706119.5
St. Louis36,7158,5643,00274.3
State College20,8115,7448,544216.9
Tallahassee8,9646,7826,249154.7
Tampa14,8377,81012,800316.8
Topeka13,2857,8804,356107.8
Tucson6,3785,4936,606163.5
Tulsa41,22511,1007,171139.5
Wakefield8,8642,53163521.6
Wichita33,73114,0007,561192.0
Wilmington (NC)8,7805,2002,11659.8
Wilmington (OH)39,26811,5005,548140.9

2 comments:

  1. While rankings are labeled on the maps, and while it is human nature to make comparisons, keep in mind that the needs and demographics of each WFO are different.twitter blue badge

    ReplyDelete
    Replies
    1. Yes indeed. It is difficult to place a ranking on a map an not draw a direct comparison. The Chicago WFO has very different needs than the Duluth WFO.

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