[Report] Social Media Analysis of Union Budget 2014 - More than 400k Mentions, Majorly Positive

The Modi government’s first budget has been a major talking point in the 7-8 weeks that the regime has been in power. Given that growth-and-development promises were central to the BJP’s LokSabha campaign, the anticipation towards the Union Budget was especially magnified. So, on the back of much hype and expectation, Finance Minister Arun Jaitley unveiled the Union Budget for 2014-15 on Thursday, 10 July.

Germin8 analyzed what the junta’s response to the budget announcements was. Social Media, as always, proved to be a data mine of information on public opinion. We gleaned that the budget has received a healthy mix of optimism and skepticism on the whole; but given the sheer breadth of issues covered, an in-depth analysis had to be carried out to comprehensively gauge people’s response to the budget.

Our analysis identified certain broad areas that appeared to have drawn the maximum attention from the junta on Social Media. The analysis tried to discern people’s sentiments towards these areas, and to identify the specific reforms/announcements that were lauded and the ones that drew criticism. Certain announcements did not appear to have received a consensus in opinion and seemed contentious from the people’s point of view.

Demographic separation also revealed that while male participation was greater than female participation in budget-related conversations, certain issues attracted a greater share of talk from the fairer sex.

A lot of buzz also surrounded the brains behind the budget: Finance Minister Arun Jaitley and Prime Minister NarendraModi. Comparisons to former Finance Ministers/Prime Ministers were widespread, along with chatter about whether or not the BJP duo had been able to live up to the public expectation.

The analysis was carried out using Germin8’s proprietary Social Listening tool. To analyze the response to each specific aspect of the budget, an ontology (knowledge structure) was created. This ontology divided the issues covered by the budget into broad areas, which were further divided into the specifics covered by each area. Public sentiment towards each issue covered by the analysis was carried out using Natural Language Processing algorithms incorporated in Explic8.

The findings from the analysis are hereby presented in the form of the following report: