NSA Tweets Rohit kumar


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Capitalizing, qualifying and quantifying the tweets about NSA on Twitter
This analysis is indicative and provides directional guidance on how NSA is perceived across the world.

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NSA Tweets Rohit kumar

  1. 1. NSA Your Secret Follower Rohit kumar Nov 2013
  2. 2. Objective, Timeframe and Source of Data Objective: Capitalizing, qualifying and quantifying the tweets about NSA on Twitter Time frame : October 2013 to November 2013 Geography: Tweets from across the world were considered for the data collection Language: Tweets which are only in English were selected after filtering other national languages Note : • For the analysis, open source Social Media monitoring tool Trackur was used. • This analysis is indicative and provides directional guidance on how NSA is perceived across the world. • The data used for analysis solely dependent on the tool used, volume of the data captures and timeframe considered for the study and human intervention to ensure data has consistency and credibility to derive inferences Source: Trackur – http://www.trackur.com/
  3. 3. How Noise was excluded from Data 1. Some tweets were in language other than English which were not considered for data analysis Example: Documentos da NSA so distribudos como segurana.https://twitter.com/BrendaGwen_/statuses/389833378029395968 2. Few Tweets were repeated multiple times which were directing us to the same source by the same user hence they were not considered for data analysis 3. Few profiles from the data were either suspended/ page doesn’t exist which are represented below: A) Example: The National Security Agency is gathering email... https://twitter.com/pRaTiK_wow/statuses/389944722925817856 B) Example: NSA Discloses Cellphone Location Tracking Tests:.. https://twitter.com/TriumphCISO/statuses/385795119053430786
  4. 4. Data Analysis : Approach and execution
  5. 5. Data Collation and Cleansing Negative Neutral Positive Total Initial data from the tool 155 603 24 782 Final data after cleansing 168 489 18 675 155 603 24 168 489 18 Negative Neutral Positive Data Cleansing Initial data from the tool Final data after cleansing 782 675 Intial data from the tool Final data after cleansing Total Tweets • After reading through the tweets we could infer that there are 107 tweets which can be considered as null/invalid based on the language, repetitive tweets, inactive links and suspended accounts. • We have listed all these invalid tweets in our reference sheet with the tab name as “Tweets –107”
  6. 6. Sentiments of the Overall Posts • The overall sentiment of posts were neutral considering the fact that they was more viral in terms of what and how NSA has been carrying out their operations, the opinions of the public are also captured along with the categories which are shared in the proceeding slides in detail Total Number of posts N=675 Negative, 25% Neutral, 72% Positive, 3% 168 489 18 Negative Neutral Positive
  7. 7. Overall Posts by Category • Most of the tweets were primarily having mentions about Obama/Govt. which has a direct correlation to NSA in the tweets that were gathered followed by the discontent by the companies which have the data of the customers which were accessed by NSA without their approval Total Number of posts N=675 55 15 21 18 566 0 100 200 300 400 500 600 Companies Countries Edward Snowden NSA Employees Obama/Govt
  8. 8. Qualitative Sentiment Analysis • Most of the tweets were centered around the way in which NSA/Obama administration has handled the entire situation, it has received most of its tweets under the sentiment as "Neutral" considering the articles which were published by the various news corporation for the knowledge of the pubic. Total Number of posts N=675 Companies Countries Edward Snowden NSA Employees Obama/Govt 8 11 4 7 138 47 4 15 11 412 2 16 Positive Neutral Negative
  9. 9. Snapshots of Tweets Examples of Twitter - sentiments
  10. 10. Overview #NSA Tweets • The National Security Agency of the United States (NSA) spied 35 phone calls from world leaders • The National Security Agency recorded information about more than 124 billion phone calls in one month • The National Security Agency has been harvesting millions of e-mail addresses from contact lists of users of sites such as Facebook, Gmail, Hotmail and Yahoo. • French Condemn Surveillance by N.S.A. • The NSA Hacked Former Mexican President Felipe Calderon’s Email While He Was In Office • The National Security Agency, the controversial U.S. surveillance agency, has had a tough few weeks, as new allegations from leaked documents have angered more allies. • Edward Snowden: US would have buried NSA warnings forever • Snowden claims Russia, China did not get NSA documents • National Security Agency has had limited success in cracking Tor communications • Government Shutdown Slows NSA Surveillance Reform Efforts: • NSA’s vast new Utah data hub suffering from ‘meltdowns’ – report • White House confirms National Security Agency (NSA) chief to step down
  11. 11. Introduction Mean while this is what White House tweeted, there is no link to view the Photo in this tweet !
  12. 12. How other Countries reacted !
  13. 13. How NSA is used by its own employees
  14. 14. NSA Website was Attacked
  15. 15. NSA — Positive tweets White House press secretary Jay Carney confirmed that National Security Agency Director Gen. Keith Alexander would step down early next year but downplayed suggestions his departure had anything to do with recent damaging leaks from Edward Snowden.
  16. 16. NSA — Neutral tweets
  17. 17. NSA — Negative (Sarcasm) tweets
  18. 18. NSA — Negative tweets
  19. 19. Manual intervention - Changed the sentiment from “Positive” to “Negative/ Neutral” – Positive to Negative Positive to Neutral Positive to Negative Positive to Neutral
  20. 20. Conclusion Neutral Based on the analysis carried out on the data we have derived the following: • Most of the articles had their reference to the twitter account of the news corporation which twitter users (individuals) have leveraged for retweeting so the sentiment remains to be neutral • There are few instances in which the tool has captured the tone in a way which the user never intended the tweet to be so we had to change the sentiments, the examples for which were already in the earlier slides • Few of the twitter users have dared to tweet about NSA directly in a tone which was Negative and few have taken an alternate route of using Sarcasm but most of them refrained from commenting hence we have most of Tweets on an Neutral Tone from the data . In conclusion we infer that the overall tweets are mostly having a “neutral "sentiment towards NSA