1) The document analyzes social media conversations around the 2014 Indian Union Budget. It tracks over 400,000 mentions on social media from July 3rd to July 10th. 2) The analysis found that discussions peaked on Budget Day, with the most activity occurring from 11am to 2pm during the finance minister's speech. The #Budget2014 hashtag was most popular. 3) Sentiment around the budget and key figures like the Prime Minister and Finance Minister was largely positive. Major positive themes included increased income tax exemptions and reforms to education, FDI, and electronics.

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2. 2
Introduction
Social Media Analysis
Methodology

3. 3
Introduction
• On the day of the much-anticipated Union Budget for 2014-15, social media was abuzz with
conversation.
• Germin8 conducted a Social Media Analysis of the whole event on social media
• This analysis tries to answer the following key questions :
• How did the audience react to the budget?
• What did the people discuss about the Finance Minister and the Prime Minister?
• What were the major themes of discussion around the event?
• What were the underlying sentiments around these themes?
• How did these conversations vary among men and women?

4. 4
Social Media Summary (1/2)
Total Mentions – 403,018
71.70%
28.30%
Gender Distribution
Male Female
41842
132933
0 20000 40000 60000 80000 100000 120000 140000
3-Jul-14
4-Jul-14
5-Jul-14
6-Jul-14
7-Jul-14
8-Jul-14
9-Jul-14
10-Jul-14
Mentions
#RailBudget
• The conversations surrounding the budget slowly gained momentum throughout the
week
• The spike on 8th July represents the Railway Budget
• As expected, the conversations peaked on the Budget Day
• Twitter remained the top medium for conversations followed by Facebook and News
Top Sources

5. 5
18289
4763
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
Male Female
Unique Authors
Male Female
Top Hashtags
trending during the
day (10th July)
#Budget2014
#ModiBudget
#SuperBudget
• Around 18,289 Unique male authors & 4,763 unique female authors were discussing the
union budget on social media
• The hashtag #Budget2014 was the most popular hashtag used on social media followed
by #ModiBudget and #SuperBudget
Social Media Summary (2/2)

6. 6
Mentions Across The Budget Day (10th July)
2714
5062
17491
18501
12844
11324
7394
3960
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
20000
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Mentions
• The buzziest hours of the day were from 11.00 pm to 02.00 pm which coincided with the
Finance Minister’s speech, thereby confirming the second screen phenomenon
• News coverage in the evening hours ensured that the conversations stretched across the
day

7. 7
Overall Sentiment Analysis
73%
27%
Positive Negative
Sentiments
Positive
• The industry experts gave the Union Budget a thumbs-up
• Concerns around allotting too many funds towards building a statue drew a lot of flak

8. 8
Brains behind the Budget
Narendra Modi Arun Jaitley
Negative Positive
31%
75%69%
25%
• Widely touted as the #ModiBudget, there were bound to be a lot of conversations around Modi
besides the jokes, the overall sentiment surrounding Modi was chiefly positive
• Arun Jaitley managed to drive positive conversations in his maiden budget speech too
81726
58827
Mentions for Ministers

9. 9
Top Themes Discussed During The Day
• Income Tax was the most widely discussed theme around the budget on Social Media.
• Announcements made in Education, FDI and Electronics were other the other major themes of
discussion
Tobacco

10. 10
Income Tax (1/2)
83.20%
16.80%
Sentiments Around Income
Tax
Positive
• The increase in exemption limit of the income tax from Rs.2 lakh to Rs.2.5 lakh for all
individuals & the exemption limit for senior citizens being increased from Rs.2.5 lakh to Rs.3
lakh was discussed with positive sentiments
• Expectations of IT exemption limit being increased to Rs 5 Lakh drew the ire of the public
9

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69.50%
30.50%
Gender Distribution
Male Female
• The chief topics of discussion within IT reforms were
increase in the tax exemption slab for all individuals
• The cap being raised to Rs 1.5 Lakh for both 80C and
PPF
• Discussion around IT reforms saw more women
participation as compared to other topics
Buzz Words
Income Tax (2/2)
10

12. 12
Education (1/2)
69.50%
29.50%
Sentiments Around
Education
Positive Negative
• Education-related reforms received positive sentiments due to the announcement of the Skill
India program – a scheme to train and skill the youth.
• The budget received a lot of flak since a lot of people felt that funds allocated for opening new
IITs and IIMs could have been utilized better in other areas
11

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Education (2/2)
68.60%
31.40%
Gender Distribution
Male Female
• Within discussions about education, institutions
such as IIMs, IITs and AIIMS received mentions
owing to the announcement to open 5 new IITs,
IIMs and 4 new AIIMS.
• The “Beti Padhao Beti Bachao” scheme for
women also garnered attention.
Buzz Words
12

14. 14
FDI (1/2)
90.40%
9.60%
Sentiments Around
FDI
Positive Negative
• The raising of the foreign investment cap in the defence and insurance sectors from 26% to 49%
was lauded by a lot of the Twitter junta.
• However, the government received criticism for having opposed FDI when in the opposition but
taking a contradictory stance now.
13

15. 15
71.30%
28.70%
Gender Distribution
Male Female
Buzz Words
• Within discussions about FDI, buzzwords
revolved around the defence sector.
• A large focus was on the impact of FDI on the
security of the country and the benefits to the
industry.
14
FDI (2/2)

16. 16
Funny Tweets
As with all things, the Twitterati did not miss the opportunity to make fun of
the union budget, and ensured hearty entertainment throughout the day.

17. 17
Methodology
• The conversations around the Budget 2014 were tracked using
Explic8, Germin8’s proprietary Social Listening tool
• An ontology (knowledge structure) of the event covering all
aspects around the union budget was created
• The conversations were then analysed by the tool to determine the
topics and associated sentiments around them
• Researchers from Germin8 then interpreted the analysis and
presented the key findings in the form of this report

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