Thursday, May 21, 2015

TV and "Brand Affinity"

Colleague Michael Castengera pointed this out, a big survey on "brand affinity" (more on this in a moment) and television news. You can see one version here (a somewhat more full PR release here). Below, one lede:
A study of news “brand affinity” finds the broadcast networks aren’t quite the fading giants many perceive them to be. The survey, by SmithGeiger on behalf of the National Association of Broadcasters, found broadcasters outperforming both digital and cable news brands.
Okay, a few comments. First, always look twice or three times or even more at a survey that just happens to find results that fall in line with the folks who paid for the survey. Oddly, the National Association of Broadcasters, best I can tell, don't mention this study on its site, even in the "newsroom" portion. Maybe their slow to get it up. It happens.

Second, what the hell is "brand affinity?" I asked Google.  One answer was:
Definition: Brand affinity is a metric that lets market researchers make predictions about how a consumer will behave. Brand affinity also adds a layer of information that is helpful when differentiating among consumers in order to accomplish market segmentation.
Which is about as bad a definition as one could hope to find. Circular, without being a circle. Another site described it as, well, really doesn't define it. Affinity is essentially liking, or affect (if you're into psychology). So how much you like a brand. Let's go with that and move on to the study itself. There's a bit of methodology, repeated below, as well as a graphic:
Polling more than 3,300 new consumers between the ages of 18 and 64, SmithGeiger compared the brand affinity of 22 broadcast, cable, and digital brands, including ABC, CBS, NBC and Fox local affiliates, Google, Facebook, Twitter, CNN, Fox News, and MSNBC.

Okay, about that graf above -- new consumers? I assume it meant news consumers, because it's hard to imagine a new 64-year-old consumer. How were they polled? Phone survey? God-awful robo-poll? Online? How did this sample match population parameters and, if not, were the data weighted? How were the questions written, how were they ordered? How was any of this damn survey conducted?

The results themselves you can see for yourself by reading the PR release. People like TV. No surprise there, for TV is very likable. Why its compared to a search engine (Google) and a couple of social media outlets (Twitter and Facebook), I'm not entirely clear on, but otherwise the results aren't really that surprising.

Especially when broadcasters paid the bill.








Friday, May 15, 2015

Eight? Really?

The state GOP convention is in Athens (where I live) for the next few days. A handful of presidential hopefuls are visiting as well, pressing the flesh, giving speeches, doing what candidates or pseudo-candidates do.

And a poll is out that looks at Georgia Republicans and who they're for. Here's a key point before we get into the results -- no poll this early means a damn thing. Still, polls are fun. Scroll down the piece and you'll see a framed brief description of the results, such as they are, or see the pdf here. It's a survey of 500 Republicans. I can't tell, yet, whether it includes cell phones or relies just on robo-landline calls. Let's set that side for a moment and get to the fascinating part, for me -- the race breakdown.

Racial Breakdown N=500

Whites: 483
Blacks: 8
Other: 9

 Wow, eight blacks in the poll. Eight. And yet, the poll reports the presidential nominee preferences of those eight people. The margin of error for those 8 respondents? About 35 percent, more or less. In other words, absolutely useless. Another interesting result, only 9 percent of respondents are ages 18-39. That makes me wonder if it wasn't a landline robo-poll, which can skew older.

Okay, but who's ahead? Here's the breakdown:

1. Mike Huckabee (18.3 percent)
2. Undecided (15.6 percent)
that's right, Undecided firmly holds onto second place
3. Ben Carson (15.4 percent)
4. Scott Walker (12.6 percent)
5. Jeb Bush (10.1 percent)

And then a bunch of others you can look up yourself.


Mock Those Academics

I read (and retweeted) a The Guardian piece a day or so ago with the following hed:

Journalism academics: mocked by the
media and stifled by universities


As a PhDweeb who's taught journalism for 24 years, I've never felt either mocked (except by my colleagues, continuously) or stifled by my university. Let's dig deeper. The subhead of the piece kinda sums up the argument:
Universities seek out practising journalists to work as academics, but they limit our opportunities by separating us into researchers and teachers
I don't believe this is a just a Brit perception. But the "Anonymous Academic" author says something interesting that you don't necessarily see in the U.S., the notion that  as pros enter the academy, they are "expected to embrace academic research, become PhD candidates, and make peer review contributions to the Research Excellence Framework (Ref)." I don't know Ref, but most universities hiring pros for the classroom, at least in the U.S., expect them to teach, do service, and engage (depending on their contract) in creative enterprises, such as journalistic works. This is true even of land-grant, Tier 1 research universities. You don't hire a top pro at my shop, the University of Georgia, and expect her to publish in Journalism and Mass Communication Quarterly, the top academic journal in my field.

To be clear, there are many of us who straddle both camps. I was a working journalist at three different daily newspapers, but I have a doctorate and I do academic research with titles required to include a colon and lots of fancy words. I am a master of multiple and logistic regression. No one knows SPSS better than I do. But I also teach basic reporting, advanced reporting, and other classes. I try to research less esoteric stuff that I can use in the classroom, but that's not a requirement. My work, for example, has focused on why people believe in conspiracy theories and whether attending to the news media helps or hurts such beliefs. I just published a big research piece in the above mentioned top academic journal on how people who use certain news outlets are surprised by their candidate losing, and the consequences of such misperceptions.

The good news is, most journalism is research. Our research/teacher camps are not brightly drawn lines, though they can be. At University of Florida, while I got my masters and PhD, you were either "grad faculty" (i.e., research), or you were not. And each side kinda looked down on the other. I doubt it's still the same, but it was obvious to the point of sad at the time I was there.

So, as more and more journalists find their way into the academy, our challenge is to find ways they can be creative and productive within the fairly strict confines of promotion and tenure and get recognition for their efforts. That's the tough part. Many big, research-oriented universities just don't know what to do with a pro. That's changing too, at least at better places, but it's a waste to expect pros who can do such marvelous classroom and creative work to labor in peer reviewed academic journals. Plus, I don't want any more competition getting published there.







Tuesday, May 12, 2015

Attention Spans

So I saw this tweet
and thought to myself, cool, someone's measured change in attention spans over time. And then I read the piece it's based on. And then I realized, no, they didn't measure anything at all. It's a single person's reading habits.

In the research biz, we call this an N of 1.

Yeah, I know, how PhDweeby of me to insist on data, on analysis, on something more than man-on-the-pixel anecdotal evidence. Well hell, I've read all the Game of Thrones books. Bought the first novel in hardback when it first came out, you HBO newbs,but even so I feel (N of 1 alert) that my attention span has decreased some thanks to my various digital devices, or maybe as I get older. Again, N of 1. In other words, completely meaningless.

We know a lot about how many people download books to various readers and tablets, and we know a lot about how few they actually finish. Again, that doesn't tell us a great deal because everyone has stacks of hardbacks and paperbacks they never finished. They're the ones gathering dust on the floor near my bedside table.

OK, my attention is waning. Time to go check email or Facebook or something more interesting than this.

 


Wednesday, May 6, 2015

Associations

As we all know from Bowling Alone and work on social capital, belonging to organizations and associations is important to our psychological well being. So how do Georgia counties stack up on this? It turns out that 2015 health data answers just this question. I extracted the data on "social associations" and ranked the counties from worst to first in parentheses the number of associations per 10,000 residents.

The Worst Counties

1. Chattahoochee (2.3)
2. Hancock (3.3)
3. Murray (4.1)
4. (tie) Clayton (4.6)
4. (tie) Lumpkin (4.6)

The Best Counties

1. Lincoln (20.7)
2. Rabun (20.2)
3. Stephens (17.4)
4. (tie) Fannin (17.0)
4. (tie) Early (17.0)

So what can we take from this? Bigger counties, like DeKalb or Fulton that dominate the greater Atlanta metroplex, aren't among the highest. Fulton, for example, is ranked 108th out of 159 counties, DeKalb is 135th.  Clarke County, where I live, is ranked 98th. Other nearby counties are Oconee (32nd), Jackson (100th), and Oglethorpe (81st). One takeaway is the vast difference, 10-fold, between the top county, at 20.7 associations per 10,000 people, and the last place county, at 2.3.  Maybe people in Lumpkin and Clayton counties just don't like one another.

If I took the time to map it out we might see more geographic trends. Or we might not. The top Georgia county is over near Savannah, the second and third place counties in the mountains. A retiree effect? That's a hypothesis worth testing.

Below, all Georgia counties and their rank. I didn't bother breaking ties because, frankly, I'm also grading papers.

 
County Assoc per 10k    Rank
Lincoln 20.7 1
Rabun 20.2 2
Stephens 17.4 3
Fannin 17.0 4
Early 17.0 5
Franklin 16.9 6
Miller 16.8 7
Seminole 15.6 8
Greene 15.5 9
Wayne 15.5 10
Towns 15.2 11
Appling 15.2 12
Ware 15.1 13
Thomas 15.0 14
Evans 15.0 15
Clinch 14.9 16
Pike 14.6 17
Warren 14.3 18
Turner 14.3 19
Taylor 14.3 20
Fayette 14.2 21
Schley 14.0 22
Jefferson 14.0 23
Bibb 14.0 24
Union 14.0 25
Bleckley 13.9 26
Calhoun 13.8 27
Mitchell 13.8 28
Randolph 13.6 29
Upson 13.5 30
Morgan 13.4 31
Oconee 13.4 32
Sumter 13.3 33
Treutlen 13.3 34
Terrell 13.3 35
Johnson 13.1 36
Glynn 13.0 37
Dawson 12.9 38
Wilkes 12.9 39
Pulaski 12.8 40
Troup 12.7 41
Elbert 12.7 42
Meriwether 12.7 43
Tift 12.7 44
Dougherty 12.6 45
Wilkinson 12.5 46
Laurens 12.5 47
Quitman 12.5 48
Habersham 12.4 49
Brooks 12.3 50
Pierce 12.2 51
Hart 12.1 52
Toombs 12.1 53
McDuffie 12.0 54
Decatur 12.0 55
Washington 12.0 56
Taliaferro 11.9 57
Chatham 11.7 58
Chattooga 11.7 59
Lamar 11.6 60
Walker 11.6 61
Butts 11.5 62
Irwin 11.5 63
Polk 11.4 64
Grady 11.4 65
Harris 11.4 66
Floyd 11.3 67
Camden 11.3 68
Spalding 11.3 69
Monroe 11.3 70
Madison 11.1 71
Putnam 10.9 72
Muscogee 10.8 73
Webster 10.7 74
Richmond 10.7 75
Jeff Davis 10.6 76
Macon 10.5 77
Gordon 10.4 78
Dade 10.3 79
Carroll 10.3 80
Oglethorpe 10.3 81
White 10.2 82
Montgomery 10.1 83
Colquitt 10.0 84
Coffee 10.0 85
Stewart 9.9 86
Candler 9.9 87
Screven 9.9 88
Dodge 9.8 89
Banks 9.8 90
Bacon 9.8 91
Telfair 9.8 92
Effingham 9.8 93
Catoosa 9.7 94
Clay 9.6 95
Bryan 9.6 96
Gilmer 9.6 97
Clarke 9.5 98
Twiggs 9.5 99
Jackson 9.4 100
Crisp 9.3 101
Lowndes 9.3 102
Haralson 9.2 103
Whitfield 9.1 104
Burke 9.1 105
Dooly 9.1 106
Berrien 8.9 107
Fulton 8.9 108
Baldwin 8.8 109
Jasper 8.8 110
Worth 8.7 111
Jenkins 8.7 112
McIntosh 8.7 113
Tattnall 8.7 114
Walton 8.5 115
Hall 8.3 116
Cook 8.3 117
Rockdale 8.0 118
Coweta 8.0 119
Heard 7.7 120
Talbot 7.7 121
Houston 7.6 122
Bartow 7.6 123
Pickens 7.5 124
Bulloch 7.4 125
Emanuel 7.4 126
Ben Hill 7.4 127
Barrow 7.4 128
Cobb 7.4 129
Jones 7.3 130
Liberty 7.3 131
Atkinson 7.2 132
Peach 7.2 133
Columbia 7.2 134
DeKalb 7.1 135
Cherokee 7.1 136
Brantley 7.0 137
Henry 6.7 138
Lanier 6.7 139
Gwinnett 6.7 140
Wilcox 6.6 141
Newton 6.6 142
Glascock 6.4 143
Crawford 6.3 144
Forsyth 6.1 145
Charlton 6.0 146
Baker 5.9 147
Marion 5.7 148
Douglas 5.7 149
Paulding 5.3 150
Wheeler 5.1 151
Echols 5.0 152
Long 5.0 153
Lee 4.9 154
Lumpkin 4.6 155
Clayton 4.6 156
Murray 4.1 157
Hancock 3.3 158
Chattahoochee 2.3 159



Tuesday, May 5, 2015

At Least He Called It Unscienific

Is your smartphone making you dumber? A question asked and answered by magazine articles a few years ago, but one raised by a local TV news reporter's story as if it's fresh.

Check out the questions, which seem more or less reasonable. Here's the real issue -- what the hell do you compare the answers to? Logic would say the same questions asked before the advent of smartphones. After all, if your point is they make us dumber, then you need a comparison group. I know, I know. Logic and TV news, not the same thing. Another way to compare this would be between people who do and do not have smartphones, but that would be so confounded by age, and maybe income, as to be useless without sophisticated statistical manipulations.

By the way, there are several here I can't answer. Clearly my smartphone has made me dumber. Then again, I doubt I could ever ask them, even before I had a smartphone -- so toss that hypothesis out the window, TV guy.

At least he called it an "unscientific survey." Thank you for that.


Monday, May 4, 2015

Georgia Farms

I like to take as many breaks as possible from grading and mess with data, which is often far more interesting than the stuff I have to grade. Today, a brief look at -- believe it or not -- farms.

So below you see how the number of Georgia farms has dramatically decreased since 1945. That big drop is really post-war, with 198k farms in 1949 and 106k by 1959.



No real surprise, right? You'd expect to see exactly that. And of course, as the number of farms has shrunk, the size of an average farm has, if not supersized, did increase over the years but then peaked in 1987 at 247 acres. It's now 229 acres.



Now if you like math, play this game. In 1945 there were 225,897 farms with an average size of 105 acres. That equals, if my calculator is correct, to 23,719,185 acres. The latest numbers for 2012 have it as 42,257 farms at an average size of 228 acres, which equals 9,634,596 acres. That's hardly a surprise as the state, especially Atlanta, has grown.