Category Archives: 2013 NJ Election

Additional Analysis from the Report on 2013 Rutgers-Eagleton Final Election Polls

Last week we released a report from Langer Research Associates commissioned by the Eagleton Institute of Politics examining the reasons for our mis-estimates of the U.S. Senate race in October and the gubernatorial race in November 2013. In addition to examining question order priming effects, which were found to be the primary cause of the mis-estimates, Langer Research Associates examined some general operational aspects of the Rutgers-Eagleton Poll to assess the degree to which any of them influenced the estimates. None of these items were found to be causes of the mis-estimates, but Langer’s assessment provides useful guidance for the Poll.

This week we provide a brief summary of the operational portions of the report, along with our responses, which in some cases include changes in some of our processes going forward. We do this as part of our commitment to transparency and our educational mission.

Likely Voter Modeling

Issue: Pre-election polls have to estimate who will vote, which is done through likely voter modelling. This means identifying through a series of questions which respondents are likely to turn out to vote and which are not.

Summary of Langer Analysis: The Rutgers-Eagleton Poll employed a series of questions including self-reported likelihood of voting, awareness of the election date (for the Special Senate election), reported last time voting, following news of the election, and attention to debates. The calculation of likely voter was applied independently to the Senate and Governor elections. The Poll employed a scoring methodology, which assigned points to each response. The likely voter modeling was conceptually sound. However the cutoff point used greatly overestimated actual turnout. Likely voter models that overstate turnout include non-voters in their vote-preference estimates, which can compromise the accuracy of these estimates.

Likely voter modeling, however, was not the culprit in the discrepancies in the 2013 Rutgers-Eagleton estimates. Constructing three tighter likely voter models with turnout estimates as low as 32 percent in the Senate race and 38 percent in the gubernatorial contest made no substantive difference in vote-preference estimates.

Rutgers-Eagleton Poll Response: The LV screens were relatively loose in these reports, due to the size of the original sample, which simply did not allow tightening screens since that would result in too small samples. The Rutgers-Eagleton Poll staff did test varying screens and found few differences, as also determined by the Langer analysis. So the looser screens were chosen for reporting. One potential revision for future LV screens would be to use propensity scoring rather than a cutoff approach, which would allow all cases where the likelihood of voting was greater than zero to remain in the sample, weighted to reflect their relative propensity to vote. One attempt to improve the estimates that was employed was an adjustment to reflect the greater likelihood of Republicans turning out, beyond what was appearing in the LV screens. Such an approach is not industry standard and should not be employed in the future. As it turned out, this adjustment made no significant difference in the estimates. But even if it improves an estimate, we agree with the Langer report that this approach departs from best practices and should not be employed.

The Rutgers-Eagleton Poll is currently involved in a broad research project to reassess the weighting process that we use, and we anticipate the results of that project will begin to be used in polls beginning in the 2014-2015 academic year.


Issue: Non-response generally results in variation between the sample that is completed and target population norms which are based on U.S. Census data. One potential problem could be incorrect weighting of the sample prior to reporting the results. The Rutgers-Eagleton Poll is a random digit dial (RDD) survey, requiring that respondents be asked if they are registered voters in order to determine if they should be included in the sample for the purposes of asking election-related questions. For both the October and November 2013 polls, those who responded that they were not registered to vote were immediately terminated, meaning no additional questions were asked. Thus the samples are of registered voters only and must be weighted to norms for registered voters.

Summary of Langer Analysis: The Langer Report suggests that it is standard practice to weight to demographic variables for the full population, not to the registered voter population. To do so would require not terminating non-registered voters and at least asking them a series of demographic questions. Since the Rutgers-Eagleton Polls analyzed here were of registered voters only, this option was not available. The registered voter sample was weighted to the Census Bureau Current Population Survey (CPS) from March 2012 using age, gender, race and ethnicity as target demographics. Had the Poll sampled all adults, the all adult sample would have been weighted to the Census’s American Community Survey (ACS), the standard source for weighting population surveys. It is important to note that the CPS registered voter norms were from the 2012 election, making them 11 months old in 2013, which means they do not capture voter registration changes that might occur during the election season.

Rutgers-Eagleton Poll Response: The Rutgers-Eagleton Poll will continue to generally weight samples to age, gender, race, and ethnicity targets for the population from which the sample is drawn. We will make sure that we are using the most recent available norms at all times. We may do more “all adult” samples which will include subsamples of registered voters, and will allow the full sample to be weighted to current ACS norms. However, in doing so we will necessarily have smaller samples of registered voters since to increase the overall sample size would require additional financial resources not currently available.

Sampling, including cell phones

Issue: Surveys of NJ residents must be based on a probability sample of landline and cell phone respondents in New Jersey. In this survey, respondents were asked if they were registered voters and were terminated if they were not. A second area of investigation is the relative share of cell phone calls placed as part of the sample. NJ has one of the lowest cell phone-only penetration levels, but nonetheless a significant number of residents cannot be reached without dialing cell phones.

Summary of Langer Analysis: The sampling process appears appropriate for both cell phones and landlines. However, the termination of non-registered voters means the sample must be weighted to norms for registered voters, which are generally less current than adult population norms. As noted above, the Langer report suggests that non-registered respondents should be retained for the collection of demographic data before termination.

Given the increasing use of cell phones and in particular the increasing proportion of cell-phone-only households in the United States, the inclusion of a robust sample of cell phones is a necessary practice. The Rutgers-Eagleton Poll uses an overlapping dual frame sample that includes a sample of cell phone respondents regardless of whether or not they have landlines. Estimates from the federal National Health Interview Survey (NHIS) indicate that, as of December 2011, 16.5 percent of New Jersey adults used cell phones only, and an additional 24.7 percent relied “mostly” on cell phones. These proportions surely have increased since then. The October and November Rutgers-Eagleton polls, using an overlapping dual frame design, included 17 percent and 23 percent cell phone interviews (weighted to 22 and 26 percent, respectively), with 4 and 7 percent cell phone-only respondents (weighted to 6 and 8 percent, respectively), well below available NHIS estimates.

Rutgers-Eagleton Poll Response: The Rutgers-Eagleton Poll has increased the cell phone target to 30 percent of the sample and will monitor whether this provides a reasonable share of cell phone-only households. We are also collecting additional information from respondents including the number of adults in the household (for landlines) and the number of adults sharing a cell phone (for cell respondents). These data will help with improving weighting calculations.

Question Wording & Field Dates

Issue: Field dates and question wording are other potential causes of differences in survey estimates.

Summary of Langer Analysis: The review finds no indication that either field dates or wording influenced Senate or gubernatorial vote preference estimates in these surveys. Question wording, while different in each survey, in all cases was balanced and neutral.

Rutgers-Eagleton Poll Response: Question wording was slightly different between the Senate and gubernatorial head-to-head questions. The biggest difference was that voters who responded don’t know in the gubernatorial question in October we not asked about which way they leaned. They were asked this in November, and the Senate vote asked about leaners in October.


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Filed under 2013 NJ Election, NJ Senate 2013 Special Election

Analysis of Rutgers-Eagleton 2013 Pre-election Polls Released

Following inaccurate results for final pre-election polls in October 2013 (NJ Special Senate) and November 2013 (NJ Governor), the Eagleton Institute of Politics commissioned an outside study by Gary Langer of Langer Research Associates of New York to identify reasons for the outcomes of these polls. Today, The Eagleton Institute of Politics and Eagleton Center for Public Interest Polling are releasing this analysis to the public as part of a commitment to transparency and education.

The Rutgers-Eagleton Poll reported a final pre-election poll for the special Senate election between then-Newark Mayor Cory Booker, a Democrat, and Republican former Bogota Mayor Steve Lonegan in which Booker held a 22-point lead. Booker ultimately won by 11 points. In the final November gubernatorial pre-election poll, Rutgers-Eagleton had Republican Governor Chris Christie ahead of his Democratic challenger state Senator Barbara Buono by 36 points: Christie won by 22.

The Langer report identifies the primary reason for the inaccurate results as the failure to put the “head-to-head” questions, which asked respondents for their vote intention, at or near the beginning of the questionnaire. Because these questions were asked after a series of other questions, it appears that respondents were “primed” to think positively about Governor Chris Christie in the November survey, which then may have led Democrats and independents in particular to over-report their likelihood of voting for the Governor. A similar process occurred with the October Senate poll, where voters were first reminded of how little they knew about Lonegan and how much they liked Booker before being asked the vote question.

Ruth B. Mandel, director of the Eagleton Institute of Politics stated that, “In response to these results, Eagleton chose to contract with an independent, highly respected, outside survey research firm to review its recent work and offer suggestions for improvement.” She added, “The Institute is committed to contributing to political knowledge in New Jersey and nationally with credible, impartial data. When we saw we had a problem, we knew we had to learn why and what to do about it.”

“Gary Langer and his colleagues spent many hours examining multiple aspects of our polling to understand what went wrong,” said David Redlawsk, director of Eagleton’s Center on Public Interest Polling (ECPIP) and professor of political science at Rutgers. “We are grateful for the efforts they put in and the advice they have provided, both in terms of this specific issue and general operations of the Rutgers-Eagleton Poll. The results of this report will make what we do even better.”

The Rutgers-Eagleton Poll has been a valued source of information about the views of New Jersey residents for over 40 years. As an academic-based survey research organization, ECPIP strives to be transparent and accessible. “We have a special obligation to take our educational mission seriously, which includes informing the public as well as learning from our own errors.” Redlawsk notes that survey research results released by the Rutgers-Eagleton Poll, for example, aim to meet the transparency standards set by the American Association of Public Opinion Research (AAPOR). Further, in recent years, the Rutgers-Eagleton Poll has been providing open informal insights and perspectives about survey research from Redlawsk and members of his staff through its blog at And for many years full data from the Poll has been freely available, generally after a one-year period, at

Langer’s major finding is that the order in which the head-to-head ballot test questions were asked most likely added inadvertent bias to the results in both the October and November Polls, although the results came out in opposite partisan directions in the two polls. Decisions made by ECPIP to maintain the standard set of questions about political figures including Cory Booker and ratings of Chris Christie at the beginning of the questionnaire worked to particularly prime Democrats in the November poll and Republicans in the October poll to support the candidate from the other party – Christie or Booker.

Redlawsk noted that the cause was a decision to maintain an ongoing four-year series of questions about Governor Christie that have been asked at the very beginning of a Rutgers-Eagleton NJ Poll since the governor’s inauguration. “We made this decision purposefully to maintain the integrity of our time series,” said Redlawsk. “This long-term research has greatly informed our understanding of public opinion about Governor Christie, and we had concerns that moving these questions after a head-to-head vote question would bias those results for the same reason we ended up biasing the vote questions.”

Most pre-election head-to-head polls focus only on the election and do not include long batteries of additional questions. The Rutgers-Eagleton Poll was unable to field separate pre-election surveys and thus combined the head-to-head polls with the regular surveys of New Jersey public opinion. “In retrospect, this was the wrong choice when one goal was to be as accurate as possible with pre-election numbers,” noted Redlawsk. “We should have either fielded a separate poll or just focused on our long-term work, rather than trying to do both at the same time.”

The Langer report on the cause of the pre-election poll mis-estimates is available to the public now on the Rutgers-Eagleton Poll website at (PDF).


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Filed under 2013 NJ Election, Buono, Chris Christie, Cory Booker, NJ Senate 2013 Special Election, Steve Lonegan

Update: Reviewing our pre-election polls

As was obvious, the Rutgers-Eagleton Poll was pretty far off on both pre-election polls last fall. In October we overstated the vote for now-Senator Cory Booker, while in November we also overstated the vote for Gov. Chris Christie. Over the last month we have been working with an outside consultant to examine our processes and results for those two pre-election polls. We anticipate having a report very soon. One thing that is very clear is that while our head-to-head vote was wrong, the other routine data we collected in those polls continued to track with both our prior results and the results of other polls at about the same time. So the focus is on our head-to-head questions, their design, and location in the questionnaire in particular, as well as our weighting strategies. In the end, we hope to be able to learn what we need to allow us to do a better job with pre-election polling.

These problems have given us pause as we move forward on our regular Rutgers-Eagleton polling. We spent a lot of time reviewing all of our numbers and benchmarks. If we had seen problems in the questions that did not ask directly about the vote (like job performance and favorability questions) we would be much much worried about our regular polls. But we do not see significant problems there. And as we run benchmarks against other polls taken at the same time, we see convergence in general, other than the vote itself.

Once we have the report from our outside consultant we will release it here. In the meantime, we are looking carefully at our newest polling results to ensure that we are confident in the numbers before we release them.

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#1 Gov Chris Christie – Rutgers-Eagleton Poll’s 2013 Top 5 Countdown

1.) Chris Christie’s banner year of unprecedented popularity ends with a reelection landslide.

Since Hurricane Sandy struck New Jersey in October 2012, Gov. Christie’s ratings have seen unprecedented highs throughout 2013, ending the year with 65 percent of voters having a favorable impression toward him, 68 percent approving of the job he is doing, and 59 percent awarding him an A or B as governor. Christie – following his own administration’s motto – has certainly been stronger since the storm, with his widely acclaimed Sandy leadership and resulting personal popularity driving his reelection victory over Democratic State Sen. Barbara Buono in this past November’s gubernatorial election. The governor easily won a second term by double-digits on Election Day against his virtually unknown, unsupported, and under-funded opponent – after a campaign year that continually showed little contest and increasingly good news from Christie, who received unparalleled support from across the political aisle, independents, women, and minority voters. Christie has become a media darling and front-page news both state and nationwide, and a 2016 presidential bid seems all but inevitable as early polling shoes him to be a top contender. The governor’s Sandy-driven success has all come in spite of New Jerseyans’ lower ratings of Christie on key issues that they deem most important in the state – 44 percent of NJ voters still disapproved of Christie’s handling of the economy and 50 percent disapproved of his job on taxes when last polled in November. Only time will tell how long the rally around Christie will last as he enters his second term and as the national spotlight placed on him continues to grow brighter.


And that’s it for our Top 5 for 2013. There were plenty of other stories over the year, and lots of additional polling. But these are the ones we think stand out.

All the best for a  Happy New Year from the Rutgers-Eagleton Poll!

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Filed under 2013 NJ Election, Chris Christie

A Closer Look by the ECPIP Staff… Gender Effects in the 2013 NJ Gubernatorial Election?

The Candidate Gender Effect That Wasn’t?
The Subtle Role Gender Played in the 2013 New Jersey Gubernatorial Election

Ashley Koning

Ashley Koning is Manager of the Rutgers-Eagleton Poll and a Ph.D. candidate in Political Science at Rutgers University.

The past election cycle in New Jersey was notable for many reasons, not least of which was that State Sen. Barbara Buono was the first woman to run for the executive office as a major party candidate since Gov. Christie Todd Whitman more than a decade ago.  It initially seemed like the governor’s race could have been the perfect storm for a gendered campaign, given Buono’s stark contrast to Gov. Christie – the very embodiment of “Jersey guy” toughness – and her partisanship, ideology, and agenda that revolved around the types of compassion and social issues frequently stereotyped as feminine, “communal,” and emotionally charged.  After all, we know through a whole host of research that the entire process is gendered for women candidates from selection through Election Day as they continue to be stereotyped – even if not intentionally – by both voters and by the media (see the Center for American Women and Politics or the Political Parity project for more on this).  Gov. Whitman even speculated decades ago that her gender affected pre-election polling during her run for governor back in 1993, consistently underestimating her eventual win (though this has been debated in the literature, both for and against).

Yet it was Gov. Christie who cried foul about his physical appearance being put in the campaign spotlight after a comment he claimed Buono made that alluded to his weight issues.  And the only gender gap the media spoke of was the one in Christie’s favor among women voters.  In a race where gender could have potentially had a significant impact, any type of gender effect from Buono’s candidacy seemed to be non-existent.

But sometimes there is more than meets the eye in these cases.  Therefore, in our final pre-election poll from October 28 – November 2, we conducted a small “list” experiment to test whether Buono’s gender actually had any effect on why respondents thought she was behind in the polls throughout the entire campaign.  For a campaign season that rarely – if ever – explicitly mentioned Buono’s gender as a pro or con to her candidacy, the results of our survey experiment paint somewhat of a different story.

First, what is a “list experiment”?

List experiments have increasingly become a popular research tool in political science as a way to unobtrusively tease out attitudes towards sensitive subjects that respondents may not want to express explicitly – whether because of a wish to sound socially desirable and not go against commonly held societal beliefs, to maintain congruency within oneself regarding other views and aspects of his or her own life, or in order to not disparage the interviewer based on perceived characteristics such as gender and race.  Respondents only become more comfortable expressing socially undesirable or unacceptable answers when a degree of anonymity can be obtained.  Therefore, survey list experiments enable this desired anonymity by allowing respondents to not have to directly state their views to the interviewer but rather provide a much more coded and private – and thus hopefully more accurate – response.

In a list experiment, the survey sample is randomly split into different groups; one group acts as the baseline or “control” condition group, while the one or more remaining groups act as the experimental condition(s) to test the sensitive issue in question.  All groups are then given a list and asked only to specify how many items on the list they would choose; those in the experimental group(s) have one additional item on their list related to the target issue than those in the control group.  Respondents then report only a number based on how many items they support or oppose, never specifying exactly which item(s) was (were) left out.

For example, we asked the following question to more subtly explore the impact of gender on Buono’s campaign:

“There has been a lot of speculation about why Barbara Buono has been so far behind Chris Christie in the polls during this entire election season.  I am going to read you three possible reasons for it. I would like to know how MANY of these reasons you agree with.  Just tell me how many, I do not need to know which ones.”

 We then split the sample in half, randomly assigning half of our respondents to each group.  The first half were given three statements about Buono in a random order and asked whether they agreed with none, one, two or all three of them:

Her views are too liberal for New Jersey.
She is not well known throughout the state.
She did not receive enough support from the Democratic Party.

The other half of the sample received the same three statements, plus a fourth statement that addressed Buono’s gender.  All four were presented in a random order, and these respondents were asked whether they agreed with none, one, two, three, or all four of them. The fourth statement was:

            She is a woman.

Since the ONLY thing that differs between the two lists is the addition of the target item in the second list, we can use some very simple statistics to see if it ha any effect, that is, to see if  some voters think Buono was disadvantaged by being a woman. Because the two groups are random, if both got the same list we should get about the same mean number of responses for both groups. But since the second group has an extra item – the target item – any difference in the mean between voters in the second group and those in the first has to be because of the extra item.

So we compare the means (averages) of both groups, and look at the difference between the first group (the “control” list) and the second group (the “experimental” list) to determine the percentage of respondents who supported or opposed the target item.  While we will not know whether individual respondents agreed or disagreed with this item, we will get a more accurate read on  how many voters felt Buono’s gender was a disadvantage than we would if we asked the question outright..

So, was there a candidate gender effect?

The short answer is yes, but a modest one.  The first “control” group that received only three items selected 1.77 items on average.  The second group – our “experimental” group – that received the four items selected 1.92 items on average.  We take the difference of these two averages and multiply it by 100 to get the percentage of respondents who actually agreed that Buono’s gender influenced her continual double-digit lag behind Christie in the polls throughout the campaign. The result is 15 percent of NJ voters thought Buono being a woman candidate contributed to her support deficit during the race.

We know that there are no significant differences in characteristics between the two random groups – such as respondent gender, age, race, partisanship, ideology, and vote choice.  Furthermore, the only difference between the experimental versions assigned to these two groups is the item specifying Buono’s gender; all other items are the same, and all items are presented in a random order.  Therefore, we can with a great deal of confidence say that this extra gender item is making the difference – and according to tests of statistical significance, this difference is not just by chance.

The Candidate Gender Effect That Not-so-evidently Was

While 15 percent may not initially seem like a large amount, that is about one in seven voters who believed Buono’s gender to be an issue in her performance during the campaign.  If we generalize this a bit to the more than two million New Jersey voters who voted for governor this past election, that means more than 300,000 voters may have believed in some way that Buono being a woman candidate contributed to her struggles.  While Buono no doubt eventually lost for a large variety of reasons – Christie’s untouchable and skyrocketing post-Sandy popularity, lack of support from Democrats at the elite and mass level, and difficulties fundraising compared to Christie’s insurmountable war chest just to name a few – her gender may be one of them despite the apparently non-existent role it seemed to play publicly.

Buono in fact did a few points better in the actual election results than in the last pre-election average forecast by Real Clear Politics, and though Christie did slightly better than the average predicted as well, Buono’s increase from the average to the actual was twice Christie’s (Christie went up 1.6 points from an average of 58.8 percent to an actual of 60.4 percent; Buono went up 3.4 points from an average of 34.7 percent to an actual of 38.1 percent).  Perhaps there is some more support here for the polls underestimating Buono in part due to gender, but the clearest takeaway here is that gender still plays a notable role in campaigns – even when it seemingly does not.

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Filed under 2013 NJ Election, Buono, Chris Christie

A Closer Look by the ECPIP Staff… Internet use in the Gubernatorial Election

The Internet, the Gubernatorial Election, and Age

Ian McGeown, Liz Kantor and Max Mescall

Ian McGeown is an Aresty Undergraduate Research Assistant with the Eagleton Center for Public Interest Polling, and is a sophomore at Rutgers University. Liz Kantor is an Aresty Undergraduate Research Assistant with the Eagleton Center for Public Interest Polling and a School of Arts and Sciences Honors Program at Rutgers University in the class of 2016. Max Mescall is a research intern at the Eagleton Center for Public Interest Polling and a junior at Rutgers University.

In recent years, the Internet has become a wealth of information on nearly every topic. For example, many politicians and institutions have a presence on a host of social media sites – such as Facebook, Twitter and YouTube – as do newspapers, who more and more frequently put their own content online. Notable generational gaps in how much news is obtained through Internet sources exist, however (for a great summary of generational differences in various online activities in general, see here: The recent gubernatorial election in New Jersey highlights this trend.

Unsurprisingly, younger generations tended to get information on the 2013 governor’s race in New Jersey through social media sites more than older generations. For 18-39 year olds, for example, 16 percent got information about the race on Twitter, while only 6 percent of 40-64 year olds did the same; no one over the age of 65 received information from the same site. Facebook also generated a similar trend, with 32 percent of those under 40 obtaining some information about the race from the site.  This is compared to only 21 percent of those between the ages of 40 and 64, and 11 percent of people 65 and older, who got information from here. Meanwhile, 26 percent of people between 18 and 39, 11 percent of those between 40 and 64, and 10 percent of people over 65 years old reported getting information off of the video sharing website YouTube.

This trend ceases, however, when it comes to “traditional” online media sources, such as online newspapers and blogs. Here, there is only a small 5-point difference between the youngest and oldest age brackets, with 15 percent of the under 40 crowd reporting that they got information on the gubernatorial election from these sources, while 10 percent of those between the ages of  40 and 64, and 13 percent of those 65 and over, state the same. These numbers suggest that it’s not necessarily using the Internet itself for election information that promotes generational gaps but rather the types of sources being accessed on the Internet.

In sum, among those who used the Internet to get information on the governor’s race, younger voters were most likely to use social media sites – particularly Facebook – more than traditional news outlet sites or blogs, as well as more likely to use social media than older voters.  Yet it also seems that everyone is using Facebook the most overall, as it was the main source of information for the governor’s race among 40-64 year olds and a close second for Internet users who are 65 and over; these Internet users in the oldest age group tended to go to blogs and news sites slightly more for their election information.  Twitter was the least popular among Internet users within each age group.

Therefore, the Internet is making it increasingly easier to get news and information about politics, but not everyone chose this method during the gubernatorial campaign season this past year – and even among those who did, differences remained in what types of sites they choose to access for information once online.  These differences are especially evident when analyzing voters by age.


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A Closer Look by the ECPIP Staff…More on the Internet and the NJ Gubernatorial Campaign

The Internet, the Gubernatorial Election, and Vote Choice

 Caitie Sullivan and Mihir Dixit

 Caitlin Sullivan is a data visualization and graphic representation intern at the Eagleton Center for Public Interest Polling and a senior at Rutgers-New Brunswick with plans to graduate in January 2014.  Mihir Dixit is also a data visualization intern. He is a first year undergraduate student in the School of Arts and Sciences at Rutgers.

Both gubernatorial candidates this past election cycle in New Jersey were quite tech savvy throughout the campaign – maintaining Twitter accounts, Facebook pages, YouTube channels, and more.  It is therefore interesting to take a look at how big a role the Internet played among the electorate and how voters differently used the Internet throughout the campaign to learn about and interact with the candidates.  While Christie’s frequent usage of the web – particularly social media – is widely known, his supporters this past election season were surprisingly not as “connected” to the Internet as their governor or Buono supporters.  Whether Twitter, Facebook, YouTube, or blogs and news sites, those Internet users who voted for Buono were more likely than Christie voters to say they used these online tools.

The differences between Christie and Buono voters in what online tools they use mainly stem from social media usage.  More Internet-using Buono voters than Christie voters used Twitter to keep track of the election – 12 percent versus 7 percent.  There was also a clear difference in the percentage of Internet-using voters for each candidate who reported using Facebook to monitor the election. Twenty-one percent of Christie voters used Facebook to acquire information about the race, versus 26 percent of Buono voters.  The widest margin between Christie voters and Buono voters was for YouTube. While the video sharing website remained unpopular with 12 percent of Christie voters, almost double the number of Buono voters – 22 percent – reported having used it as an informational resource.  Christie and Buono voters were more similar in their use of blogs or news websites: 12 percent of Christie voters and 13 percent of Buono voters said they used this source for election-related news.

These differences in online sources are most likely attributable to the different characteristics underlying Christie voters and Buono voters and not necessarily directly to the vote choice itself.  Despite Christie’s frequent activity online, his supporters – many who are Republicans like Christie – tend to be older and therefore not as likely to use the Internet and especially social media.  Buono supporters, on the other hand, are made up of mainly Democrats and younger voters, who are especially prone to using the Internet.  Therefore, the differing usage of these various Internet tools between Christie voters and Buono voters may be more about the demographics typically most associated with each candidate’s party than simply who they would vote for in the election.


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Filed under 2013 NJ Election, NJ Voters