2. Twitter
• Create and share ideas and information without barriers
• Free social networking and micro-blogging site
• Users sent 140 character long text messages
4. Online
Communication, Offline
Behavior slurs correlate with lower vote tallies for
• Searches for ethnic
minority politicians
• Film title mentions correlate with revenue
• Online expressions of public mood correlate with fluctuations
in stock market prices
• Sophisticated models for individual and group behavior
5. Twitter Can Predict US
Elections
• Fabio Rojas, Published on August 12, 2013, Indiana
University professor from Department of Sociology
• Digital democracy
• “Modern politics happens when somebody comments on
Twitter or links to a campaign through Facebook”
• extracted 542,969 tweets
• predicted the winner in 404 out of 435 competitive
candidate for Congress in 2010
http://www.washingtonpost.com/opinions/how-twitter-can-predict-an-election/2013/08/11/35ef885a-0108-11e3-96a8d3b921c0924a_story.html?wpisrc=emailtoafriend
6. Kejriwal VS Modi on Social Media
• “Arvind Kejriwal has better engagement on social
media, Narendra Modi has twice the numbers” 15th Feb 2014 in
Indian Express
•
•
•
•
•
Total number of followers
Daily increase in followers
Number of fake followers
Tweets per day
Topics
http://indianexpress.com/article/india/politics/arvindkejriwal-narendramodi-social-media/
7. Why does this happen?
• People talks +ve/-ve
• all publicity is good publicity
8. More Tweets, More Votes
• 537,231,508 tweets between Aug 1 to Nov 1, 2010 and
3,032,823,110 tweets between August 1 and November 5, 2012
• extracted 113,985 tweets in 2010 and 428,984 in 2012 that
contain name of the Republican or Democratic candidate
• 28,193 users in 2010 and 166,978 users in 2012
• For each candidate computed tweets that include their names
DiGrazia J, McKelvey K, Bollen J, Rojas F (2013) More Tweets, More Votes: Social Media as a Quantitative Indicator
of Political Behavior. PLoS ONE 8(11): e79449. doi:10.1371/journal.pone.0079449
9. Analysis
• Ordinary Least Squares regression (OLS) to estimate the effect
Twitter share on vote margin
• Uses a bivariate model and a full model to estimate effect of
the tweet and user share variables
10. Tweet Share
• tws(i) : the amount of Twitter attention given to a particular
candidate over their opposition in a particular race
• i : district
• twD(i) and twR(i) : Democratic and Republican frequencies
11. Figure 1. 2010 Republican Tweet Share vs. Vote Share.
DiGrazia J, McKelvey K, Bollen J, Rojas F (2013) More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior.
PLoS ONE 8(11): e79449. doi:10.1371/journal.pone.0079449
http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079449
12. Figure 2. 2012 Republican Tweet Share vs. Vote Share.
DiGrazia J, McKelvey K, Bollen J, Rojas F (2013) More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior.
PLoS ONE 8(11): e79449. doi:10.1371/journal.pone.0079449
http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079449
13. Part of Tweet
• Tweet (Unique identifier, the text of the tweet, tweet
time, the username, case of retweets or mentions the account
names of the other users associated with the tweet)
14. Part of Tweet
• Emoticons : facial expressions pictorially represented using
punctuation and letters
• WATCH: #Malala witnesses the arrival of Syrian @refugees in
Jordan in this moving video from #UNHCR http://uni.cf/1c35eyV
• Target/Mention : Users of Twitter use the “@” symbol to refer
to other users
• Hashtags : Users usually use hashtags to mark topics
15. Acronyms
• Acronym English expansion
•
•
•
•
•
•
•
gr8, gr8t
lol
rotf
bff
4U
Ab
Gud
Great
Laughing out Loud
Rolling on the floor
Best Friend Forever
For you
About
Good
20. References
• DiGrazia J, McKelvey K, Bollen J, Rojas F (2013) More
Tweets, More Votes: Social Media as a Quantitative
Indicator of Political Behavior. PLoS ONE 8(11): e79449.
doi:10.1371/journal.pone.0079449
• http://www.statisticbrain.com/twitter-statistics/
Twitter wont need any introduction. We all r fimilarwid it. It connect us wid world, to our frnds, n family. Do the small tweets posted on twitter are of any value. Do twitter data is possible to analysis and is it benificial?
Create and share ideas and information instantly, without barriersA key feature of this platform is that, by default, each user’s stream of real-time posts is public. This fact, combined with its substantial population of users renders Twitter an extremely valuable resource for commercial and political data mining and research applications.
On twitter People write, express themselves, which now represents a new frontier for the study of human behavior.
there is a growing literature suggesting that online communication can be a valid indicator of offline behavior of ppl.
We believe that Twitter and other social media reflect the underlying trend in a political race that goes beyond a district’s fundamental geographic and demographic composition. If people must talk about you, even in negative ways, it is a signal that a candidate is on the verge of victory. The attention given to winners creates a situation in which all publicity is good publicity.
More Tweets, More Votes: Social Media as a Quantitative Indicator of Political Behavior
Simple linear regression lives up to its name: it is a very straightforward approach for predicting a quantitative response Y on the basis of a single predictor variable X. It assumes that there is approximately a linear relationship between X and Y .Simple regression y~mx+n (3.1) m,n are coefficients.In practice, β0/m and β1/n are unknown. So before we can use (3.1) to make predictions, we must use data to estimate the coefficients. Let(x1, y1), (x2, y2), . . . , (xn, yn) represent n observation pairs, each of which consists of a measurement of X and a measurement of Y .Our goal is to obtain coefficient estimates ˆ β0 and ˆ β1 such that the linear model (3.1) fits the available data well—that is, so that yi ≈ ˆβ0 + ˆ β1xi for i = 1, . . . , n. In other words, we want to find an intercept ˆ β0 and a slope ˆ β1 such that the resulting line is as close as possible vote sharing/y.The R2 statistic provides an alternative measure of fit. It takes the form of a proportion—the proportion of variance explained—and so it always takes on a value between 0 and 1, and is independent of the scale of Y . To calculate R2, we use the formulaR2 = TSS − RSS / TSS= 1− RSS/TSSwhere TSS =(yi − ¯y)2 is the total sum of squares, and RSS is defined total sum of in (3.16). TSS measures the total variance in the response Y , and can be squares thought of as the amount of variability inherent in the response before the regression is performed.R2 measures the proportion of variability in Y that can be explained using X.
Hashtag : short tokens used to indicate the topic or intended audience of a tweet
