posts about or somewhat related to ‘polling’

We continue to find that Democrats trust most TV news sources other than Fox, while Republicans don’t trust anything except Fox. News preferences are very polarizing along party lines.

Dean Debnam, President of Public Policy Polling, in a press release on a new poll released on American trust in its broadcast news stations. Fox News’ Credibility Declines (PDF).

The News: Americans don’t trust broadcast news sources. Matter of fact, more people distrust NBC, ABC, CBS, CNN, MSNBC, Fox News and Comedy Central than trust them.

However, Fox News is the news org that Americans are most skeptical about. According to the PPP poll, 46% of voters distrust it while 41% trust it.

The only news org that a majority does trust? PBS, with 52% of voters saying they trust it and 29% saying they don’t.

The [New York] Times does not release traffic figures, but a spokesperson said yesterday that [Nate] Silver’s blog provided a significant—and significantly growing, over the past year—percentage of Times pageviews. This fall, visits to the Times’ political coverage (including FiveThirtyEight) have increased, both absolutely and as a percentage of site visits. But FiveThirtyEight’s growth is staggering: where earlier this year, somewhere between 10 and 20 percent of politics visits included a stop at FiveThirtyEight, last week that figure was 71 percent.

But Silver’s blog has buoyed more than just the politics coverage, becoming a signifiant traffic-driver for the site as a whole. Earlier this year, approximately 1 percent of visits to the New York Times included FiveThirtyEight. Last week, that number was 13 percent. Yesterday, it was 20 percent. That is, one in five visitors to the sixth-most-trafficked U.S. news site took a look at Silver’s blog.

Marc Tracy, The New Republic. Nate Silver Is a One-Man Traffic Machine for the Times.

Takeaway: Stat nerds have clout.

Nate Silver on the Colbert Report

The New York Times’s Nate Silver, creator of the influential 538 election forecasting blog, talks pundits versus statistics, and how probability drives his forecasting methodology. 

He has no love for pundits, and says that given the choice between them and Ebola, he’d go with Ebola.

Bonus: Want more on electoral polling? Jihii has a great piece on what it all means, and where it can go so wrong.

The Twitter Political Index
Via Twitter:

Today, we’re launching the Twitter Political Index, a daily measurement of Twitter users’ feelings towards the candidates as expressed in nearly two million Tweets each week…
…Each day, the Index evaluates and weighs the sentiment of Tweets mentioning Obama or Romney relative to the more than 400 million Tweets sent on all other topics. For example, a score of 73 for a candidate indicates that Tweets containing their name or account name are on average more positive than 73 percent of all Tweets.
Just as new technologies like radar and satellite joined the thermometer and barometer to give forecasters a more complete picture of the weather, so too can the Index join traditional methods like surveys and focus groups to tell a fuller story of political forecasts. It lends new insight into the feelings of the electorate, but is not intended to replace traditional polling — rather, it reinforces it.
For example, the trend in Twitter Political Index scores for President Obama over the last two years often parallel his approval ratings from Gallup, frequently even hinting at where the poll numbers are headed. But what’s more interesting are the periods when these data sets do not align, like when his daily scores following the raid that killed Osama bin Laden dropped off more quickly than his poll numbers, as the Twitter conversation returned to being more focused on economic issues.
By illustrating instances when unprompted, natural conversation deviates from responses to specific survey questions, the Twitter Political Index helps capture the nuances of public opinion.

Twitter’s @gov team is creating the Index with two polling firms and data analysts from Topsy.
Image: Partial screenshot of the Twitter Political Index.

The Twitter Political Index

Via Twitter:

Today, we’re launching the Twitter Political Index, a daily measurement of Twitter users’ feelings towards the candidates as expressed in nearly two million Tweets each week…

…Each day, the Index evaluates and weighs the sentiment of Tweets mentioning Obama or Romney relative to the more than 400 million Tweets sent on all other topics. For example, a score of 73 for a candidate indicates that Tweets containing their name or account name are on average more positive than 73 percent of all Tweets.

Just as new technologies like radar and satellite joined the thermometer and barometer to give forecasters a more complete picture of the weather, so too can the Index join traditional methods like surveys and focus groups to tell a fuller story of political forecasts. It lends new insight into the feelings of the electorate, but is not intended to replace traditional polling — rather, it reinforces it.

For example, the trend in Twitter Political Index scores for President Obama over the last two years often parallel his approval ratings from Gallup, frequently even hinting at where the poll numbers are headed. But what’s more interesting are the periods when these data sets do not align, like when his daily scores following the raid that killed Osama bin Laden dropped off more quickly than his poll numbers, as the Twitter conversation returned to being more focused on economic issues.

By illustrating instances when unprompted, natural conversation deviates from responses to specific survey questions, the Twitter Political Index helps capture the nuances of public opinion.

Twitter’s @gov team is creating the Index with two polling firms and data analysts from Topsy.

Image: Partial screenshot of the Twitter Political Index.

Modeling Election Forecasts the FiveThirtyEight Way
Via Slashdot:

Years ago Nate Silver of FiveThirtyEight.com, a blog seeking to educate the public about elections forecasting, established his model as one of the most accurate in existence, rising from a fairly unknown statistician working in baseball to one of the most respected names in election forecasting. In this article he describes all the factors that go into his predictions. A fascinating overview of the process of modeling a chaotic system.

FJP: It is fascinating.
With national, regional and statewide polling feeding off oftentimes conflicting information, and then still other polling that has what Silver calls “house effects" (meaning that a poll is an outlier, skewing Democratic or Republican in relation to other polls), all within what will be a tight, tight, tight race, Silver lays out both the art and science of his models.
For example, take Silver’s analysis of Florida:

Right now, the polls there show almost an exact tie. But the model views Florida as leaning toward Mr. Romney, for several reasons.
First, the polls showing a tie there were mostly conducted among registered voters rather than likely voters. Republicans typically improve their standing by a point or two when polling firms switch from registered voter to likely voter polls, probably because Republican voters are older, wealthier, and otherwise have demographic characteristics that make them more reliable bets to turn out. The model anticipates this pattern and adjusts for it, bolstering Mr. Romney’s standing by a point or two whenever it evaluates a registered-voter poll.
In addition, the fundamentals somewhat favor Mr. Romney in Florida. The state has been somewhat Republican-leaning in the past, and its economy is quite poor. Mr. Romney has raised more money than Mr. Obama there, and its demographics are not especially strong for Mr. Obama. The model considers these factors in addition to the polls in each state. In the case of Florida, they equate to Mr. Romney having about a 60 or 65 percent chance of winning it, and Mr. Obama probably has easier paths to 270 electoral votes.

If you’re a political junky whose heart skips a beat with the daily polls, read through. As said before, it’s a fascinating look at how political forecasting is done by one of the best in the business.
Image: While US presidential politics — and its electoral college — is a winner take all system that leads to strict Red State versus Blue State divisions across the country, this map of the 2008 presidential elections provided by the University of Michigan’s Mark Newman shows that if you look at the country at a county by county level, the country’s political leanings are decidedly purple. Meaning that slight ebbs can turn an entire state red (Republican) or blue (Democratic).

Modeling Election Forecasts the FiveThirtyEight Way

Via Slashdot:

Years ago Nate Silver of FiveThirtyEight.com, a blog seeking to educate the public about elections forecasting, established his model as one of the most accurate in existence, rising from a fairly unknown statistician working in baseball to one of the most respected names in election forecasting. In this article he describes all the factors that go into his predictions. A fascinating overview of the process of modeling a chaotic system.

FJP: It is fascinating.

With national, regional and statewide polling feeding off oftentimes conflicting information, and then still other polling that has what Silver calls “house effects" (meaning that a poll is an outlier, skewing Democratic or Republican in relation to other polls), all within what will be a tight, tight, tight race, Silver lays out both the art and science of his models.

For example, take Silver’s analysis of Florida:

Right now, the polls there show almost an exact tie. But the model views Florida as leaning toward Mr. Romney, for several reasons.

First, the polls showing a tie there were mostly conducted among registered voters rather than likely voters. Republicans typically improve their standing by a point or two when polling firms switch from registered voter to likely voter polls, probably because Republican voters are older, wealthier, and otherwise have demographic characteristics that make them more reliable bets to turn out. The model anticipates this pattern and adjusts for it, bolstering Mr. Romney’s standing by a point or two whenever it evaluates a registered-voter poll.

In addition, the fundamentals somewhat favor Mr. Romney in Florida. The state has been somewhat Republican-leaning in the past, and its economy is quite poor. Mr. Romney has raised more money than Mr. Obama there, and its demographics are not especially strong for Mr. Obama. The model considers these factors in addition to the polls in each state. In the case of Florida, they equate to Mr. Romney having about a 60 or 65 percent chance of winning it, and Mr. Obama probably has easier paths to 270 electoral votes.

If you’re a political junky whose heart skips a beat with the daily polls, read through. As said before, it’s a fascinating look at how political forecasting is done by one of the best in the business.

Image: While US presidential politics — and its electoral college — is a winner take all system that leads to strict Red State versus Blue State divisions across the country, this map of the 2008 presidential elections provided by the University of Michigan’s Mark Newman shows that if you look at the country at a county by county level, the country’s political leanings are decidedly purple. Meaning that slight ebbs can turn an entire state red (Republican) or blue (Democratic).

Can Facebook Tell Us Anything About Voter Sentiment?
Politico and Facebook are teaming to analyze users’ views of candidates in the Republican primaries. Sounds interesting, but is what’s being measured — sentiment — a useful indicator of voter intent without follow-up questions?
First, via Facebook: 

Facebook will compile mentions of the candidates in U.S. users’ posts and comments as well as assess positive and negative sentiments expressed about them. Facebook’s data team will use automated software tools frequently used by researchers to infer sentiment from text.

But measuring sentiment might not tell political junkies much. TechPresident’s Micah Sifry thinks it a neat parlor trick but largely bogus as a valuable indicator.
Via TechPresident:

Here’s the issue: Counting the number of times a candidate’s name is mentioned on social media and noting what words appear alongside those mentions can illuminate broad trends. You can report that “more people talked about Candidate X today” and “Y percent of that group used word ZZZZ in their comment.” But you can’t make any kind of meaningful judgment about what those people intended by that usage without asking them.
Someone who writes “I’m so happy that Newt Gingrich is staying in the race” might be a genuine Gingrich fan, or they might be someone who hates him, but likes that he’s staying in the race because he’s entertaining, or because they think he’s hurting the Republican field. But “sentiment analysis” is still such an embryonic field that serious researchers tend to avoid any hard claims about whether such a statement is positive, negative or neither.

TechPresident’s critique runs much more sophisticated than what we post here so give it a read before following every rise and fall of voter sentiment.
Image: Negative Facebook Mentions by Candidate, December 13 to January 10, via Facebook.
H/T: @lorakolodny.

Can Facebook Tell Us Anything About Voter Sentiment?

Politico and Facebook are teaming to analyze users’ views of candidates in the Republican primaries. Sounds interesting, but is what’s being measured — sentiment — a useful indicator of voter intent without follow-up questions?

First, via Facebook

Facebook will compile mentions of the candidates in U.S. users’ posts and comments as well as assess positive and negative sentiments expressed about them. Facebook’s data team will use automated software tools frequently used by researchers to infer sentiment from text.

But measuring sentiment might not tell political junkies much. TechPresident’s Micah Sifry thinks it a neat parlor trick but largely bogus as a valuable indicator.

Via TechPresident:

Here’s the issue: Counting the number of times a candidate’s name is mentioned on social media and noting what words appear alongside those mentions can illuminate broad trends. You can report that “more people talked about Candidate X today” and “Y percent of that group used word ZZZZ in their comment.” But you can’t make any kind of meaningful judgment about what those people intended by that usage without asking them.

Someone who writes “I’m so happy that Newt Gingrich is staying in the race” might be a genuine Gingrich fan, or they might be someone who hates him, but likes that he’s staying in the race because he’s entertaining, or because they think he’s hurting the Republican field. But “sentiment analysis” is still such an embryonic field that serious researchers tend to avoid any hard claims about whether such a statement is positive, negative or neither.

TechPresident’s critique runs much more sophisticated than what we post here so give it a read before following every rise and fall of voter sentiment.

Image: Negative Facebook Mentions by Candidate, December 13 to January 10, via Facebook.

H/T: @lorakolodny.