Analyst’s Prediction: Amazon will buy Target http://ow.ly/VDhv30hxna2
69 Americans killed annually, on average, by lawnmowers – compared to 2 Americans killed annually, on average, by immigrant Jihadist terrorists http://ow.ly/1ShA30hkqSr
Indian Prime Minister Narendra Modi in a surprise move on 8th November 2016 declared the two largest currency bills (Rs. 1000 and Rs. 500) illegal. This action is primarily targeted towards reducing fake currency that’s in circulation in India and the massive amount of black money that corrupt people hold. It’s too early to discuss whether the move is good or bad. However, it doesn’t stop people from giving their opinions.
There are two primary hashtags on Twitter that are in use – #demonetization and #demonetisation. Note the difference in the spelling. The first is Americal English and the second is British English. I thought it might be interesting to analyze the tweets that used one over the other hashtag. It’s possible that some people used both but the chances are that they didn’t because the hashtags are long and take up too much space.
My hypothesis was that the tweets with hashtags with British spelling will be more negative because they are likely to originate from India. Like the people in most countries, Indians are also quite vocal on Twitter. Besides it is massively gamed by all the political parties. Currently all the opposition parties in India have opposed the move so I expected that they must be funding negative publicity on Twitter. They are likely to use the hashtag with British spelling.
On the other hand, many non resident Indians are likely to be unaffected by this move. The apparent benefits to the economy are large while the cost to individuals who don’t live in India is small. So the people who are using the Americam spelling are likely to be more positive about demonetization.
However, many foreign publications such as CNN, NY Times, WaPost, etc. may also tweet about this with the American hashtag. From my past experience, these publications have a severe bias against righ wing parties and Modi in general. This will likely make the comparison more difficult.
I downloaded 5,000 tweets for each hashtag. After cleaning the tweets and running a simple text analysis for identifying the sentiment as positive, negative, or neutral, this is what I found.
So we have almost twice as much tweets with positive sentiment for demonetization. Note that these tweets used the American English spelling. Now let’s take a look at the British spelling.
Well, I get the samle pattern with about double the tweets with positive sentiment than negative sentiment! So I can’t reject the null hypothesis of no difference. In other words, this will always remain a blog post 😉
Just for fun, I also plotted the wordcloud for both.
I was trying out a cool new R package forbesListR, which lets you download lists from Forbes website. The package still needs a lot of work but I could download data on India’s 100 richest people from 2012 to 2015. As I was playing around with the data, I decided to plot it out using the following ggplot2 code
library(forbesListR) library(dplyr) library(ggplot2) library(scales) library(ggthemes) ggplot(a, aes(x=reorder(name,rank),y=net_worth.millions,fill=year2)) + geom_bar(stat=&quot;identity&quot;,position = position_dodge(width=0.9)) + geom_text(aes(label=scales::comma(net_worth.millions), angle=90), position = position_dodge(width=0.9),vjust=0.2,hjust= 1.2,color=&quot;white&quot;) + theme_fivethirtyeight() + scale_y_continuous(labels = scales::comma) + xlab(&quot;Name&quot;) + ylab(&quot;Net Worth in Million $&quot;) + guides(fill=guide_legend(title=NULL)) + ggtitle(&quot;Net Worth in Million $&quot;)
In my code, “a” was the edited list of 10 richest Indians.
I deleted Hinduja family and Godrej family from the data although they were in the top 10 and instead decided to focus on individuals. You can download the data from here.
Mukesh Ambani is still the richest Indian although Dilip Shangvi is a close second. I thought that Gautam Adani’s rise in 2014 and 2015 is quite interesting. Similarly, Cyrus Poonawalla has increased its net worth substantially in these two years. On the other hand, Laxmi Mittal lost more than $ 4.5 billion due to falling steel prices.
Finally, Shiv Nadar of HCL increased his worth from $5.6 billion in 2012 to a staggering $12.9 billion in 2015. I think he has been a clear winner.
Below you will find a subset of slides I used in my social media marketing master class on 5th December 2013.
I am quite lazy when it comes to updating my blogs. Turns out that even after writing just 12 blog posts this year, I still attracted 5,000+ readers. Here is a summary of this year.
The WordPress.com stats helper monkeys prepared a 2012 annual report for this blog.
Here’s an excerpt:
600 people reached the top of Mt. Everest in 2012. This blog got about 5,300 views in 2012. If every person who reached the top of Mt. Everest viewed this blog, it would have taken 9 years to get that many views.
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