Statistics -- Watson-Durbin Analysis Of Term Paper

Length: 10 pages Sources: 5 Subject: Education - Computers Type: Term Paper Paper: #88914988 Related Topics: Text Messaging, Regression Analysis, Myspace, Spss
Excerpt from Term Paper :

Again, the presidential campaign acted as a catalyst for technology adoption, and led to first-time social networking users getting online. It also led to existing users creating additional profiles as well.

On the third most significant variable in determining the effects of social networks on which candidate would eventually win Q39. Do you have a single profile on each site, or do you have multiple profiles on one web site? Provides the most fascinating data from the three variables included in the analysis. Notice that the distribution of results is bifurcated from one spectrum to the other. This signals that through the use of the participative aspects of social networks, candidates were able to get the support of the top 5% of social networkers, as evidenced by having more than one profile on a given network. The mean value of this variable is 1.17 and it has a mode of 1, which again shows that the presidential campaign had the impact of creating higher adoption of social networks, with those early adopters being Obama voters.

When all three variables are taken together it is apparent that Obama's use of Web 2.0 technologies and social networks significantly increased the adoption of these technologies and websites. The data also shows that Obama, by using social networking as a core part of his strategy, adopted early adopters of other technologies as well. The use of cell phones for testing is an example

Analysis of relationships and their role in getting texts from the candidates shows that for variables 30B, 30C and 30D Obama dominates the cross-tabulation tables for the analysis. Literally, no one received text messages in any of the categories reflected by questions 30B, 30C and 30D from John McCain. This dramatically underscores how effective Web 2.0 technologies are as a means of connecting with and staying in contact with voters over a campaign.

Relationships in the Data

Appendix B provides a correlation analysis of the variables Q16, Q38, Q39 and Q41. The results show that at the .01 level of confidence that Q16 is the leading indicator of whether a respondent is pre-disposed to vote for Obama vs. McCain. Across the demographic factors and use of technologies for conventional tasks, there is no statistically significant difference between Obama and McCain voters at either the .01 or .05 levels. Only in the areas of social networking participation is the significant most prevalent and where there is a high level of statistical significance to the use of social networks for campaigning and the development of a voter base. The use of social networks as a catalyst for creating more participating online has been proven to be predictive of a candidates' ability to win an election based on this analysis.

Using regression analysis and Analysis of Variance (ANOVA), it becomes clear that the greater the level of familiarity or mastery of social networks, the greater the tendency to align with Obama's social media strategy. This is evident in the ANOVA completed that takes VOTE01 (Who the respondent would vote for) and completing regression and ANOVA analysis of variables Q16, Q38 and Q39. The following tables and scatterplots illustrate this point. What is also significant about this finding is that Obama, acting as an evangelist for social networks by accident actually galvanized the early adopters to create profiles for the first time, while also attracting the most experienced users of social networks who had multiple profiles on the same site.

ANOVAb

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

5.907

2

2.953

.769

.464a

Residual

3.840

Total

a. Predictors: (Constant), Q39. Do you have a single profile on each site, or do you have multiple profiles on one web site?, Q38. How many total profiles do you have online, counting all web sites?

b. Dependent Variable: Vote01. If the 2008 presidential election were being held TODAY and the candidates were [ROTATE: (Barack Obama, the Democrat,) and (John McCain, the Republican,)] who would you vote for?

The most significant factor of the three is how many profiles a respondent has on a social networking site prior to being interviewed as part of the study. The effects of self-efficacy or self-learning of how to navigate social networking sites makes candidates' fan pages on Facebook much more approachable and therefore, drives...

...

What is significant about the following scatterplot is the polarity of it. Obama was able to capitalize on this polarity, in effect driving greater division between those who were social network-savvy and those that weren't, yet created a brand experience as a candidate that further social networking use. In effect his brand as a candidate fostered early adoption of social networking sites and also won the key influencer group of those with multiple profiles on the same site. The role Obama as a social networking evangelist is clear in the scatterplot as well, when analyzed across several different regression techniques.

IV. Summary

There are many factors that influence an election the magnitude of the U.S. presidential race in 2008. Yet the mobilization of younger voters, combined with the ability to recruit early adopters of technology, significantly improved, to the .01 level, the ability of Obama to use these channels of communication interactively and gain more votes. The data suggest that Obama became an accidental evangelist for social networks, in effect promoting them at the same time as promoting his campaign. That can be seen in an analysis of the use of social networks by Obama voters controller for the number of years they have been on the Internet.

Obama was very successful in equating civic and national duty to vote with enrolling in social networks, a key point found in the activity on the three core variable sin this analysis. The reliance on social networks, specifically Facebook, the ability to reach those voters predisposed to voting for him through text messaging, and also creating a platform of interactive communication further distanced Obama from McCain. The data suggest that the old school approaches of face-time and working through campaigns with a balance of personal and online visits is not enough. The need for having an always-on, continually working social media strategy is essential for any campaign to succeed. Obama won the election due to these factors and the ability to use social networks to mobilize those younger voters who had not been online or used social networks before. In equating social network participating with civic duty, Obama was able to lock in a strong voter base and win the election.

References

Tim O'Reilly. (2006, July). Web 2.0: Stuck on a Name or Hooked on Value? Dr. Dobb's Journal, 31(7), 10.

Williams, C., & Gulati, G.. (1 August). Social Networks in Political Campaigns: Facebook and Congressional Elections 2006, 2008. SSRN Working Paper Series

Source of dataset for analysis:

http://pewinternet.org/Shared-Content/Data-Sets/2008/May-2008 -- Cloud-computing-politics-and-adult-social-networking.aspx

Appendices

Spring Tracking Survey 2008: http://pewinternet.org/~/media/Files/Data%20Sets/2009/May_2008_Topline.zip.zip

Appendix B

Correlations

Q38. How many total profiles do you have online, counting all web sites?

Q39. Do you have a single profile on each site, or do you have multiple profiles on one web site?

Q41. How often do you visit the social network web site where you have a profile/the social networking web site with the profile you use most often?

Vote01. If the 2008 presidential election were being held TODAY and the candidates were [ROTATE: (Barack Obama, the Democrat,) and (John McCain, the Republican,)] who would you vote for?

Q16. Have you ever created your own profile online that others can see, like on a social networking site like MySpace, Facebook or LinkedIn.com?

Q38. How many total profiles do you have online, counting all web sites?

Pearson Correlation

1

.288**

.099**

.083**

.a

Sig. (2-tailed)

.000

.000

.007

.000

Sum of Squares and Cross-products

54.946

.000

Covariance

3.342

.095

.298

.268

.000

N

Q39. Do you have a single profile on each site, or do you have multiple profiles on one web site?

Pearson Correlation

.288**

1

-.112**

-.062

.a

Sig. (2-tailed)

.000

.007

.216

.000

Sum of Squares and Cross-products

54.946

82.766

-33.307

-18.761

.000

Covariance

.095

.143

-.057

-.048

.000

N

Q41. How often do you visit the social network web site where you have a profile/the social networking web site with the profile you use most often?

Pearson Correlation

.099**

-.112**

1

-.058

.a

Sig. (2-tailed)

.000

.007

.059

.000

Sum of Squares and Cross-products

-33.307

-185.030

.000

Covariance

.298

-.057

2.709

-.174

.000

N

Vote01. If the 2008 presidential election were being held TODAY and the candidates were [ROTATE: (Barack Obama, the Democrat,) and (John McCain, the Republican,)] who would you vote for?

Pearson Correlation

.083**

-.062

-.058

1

.067**

Sig. (2-tailed)

.007

.216

.059

.000

Sum of Squares and Cross-products

-18.761

-185.030

28252.496

Covariance

.268

-.048

-.174

5.160…

Sources Used in Documents:

References

Tim O'Reilly. (2006, July). Web 2.0: Stuck on a Name or Hooked on Value? Dr. Dobb's Journal, 31(7), 10.

Williams, C., & Gulati, G.. (1 August). Social Networks in Political Campaigns: Facebook and Congressional Elections 2006, 2008. SSRN Working Paper Series

Source of dataset for analysis:

http://pewinternet.org/Shared-Content/Data-Sets/2008/May-2008 -- Cloud-computing-politics-and-adult-social-networking.aspx


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