ALS Ice Bucket Challenge

Submitted by: Shailendra Kumar, SIOM, Nasik

Email id: kumar.shailen.005@gmail.com/07276431871

ALS Ice Bucket Challenge – Sentiment Analysis

The given data consists of over 2, 00,000 of tweets. A sample of around 1, 30,000 of

tweets were taken for sentiment analysis. The analysis consisted of a sequence of steps which

follows as:-

Cleaning of data

o Tweets having blank spaces are removed

o Removing duplicate tweets

Observing the trends of tweets(data consisted of majority of tweets) for full one

month

Observing the unique thing happening over a period of time which helped ALS going

viral (for eg. keywords, timing of tweet etc.)

Reactions of people over a period of time in terms of

o Following

o Followers

o Timing of tweet

o Words used in phrases

o Positive, neutral, negative sentiments

Assumptions considered before moving forward with analysis

A sample of tweets of approximately 1, 30, 000 is used for analysis where it is

assumed that sample data will have similar sentiments as that of population data

sentiments

There are only three types of sentiments positive, negative and neutral

Sentiment Analysis

Hypothesis

ALS Ice Bucket challenge went viral because of positive sentiments in tweets

ALS Ice Bucket challenge was successful because of active participation from people around

the globe (eg. #accepting, #challenge, #love etc.)

SEQUENCES

DATA PRIEMERE LEAGUE

ALS Ice Bucket Challenge

Methodology

Based on tweets

Publicly available tool “Semantria for excel” (free account) is used for sentiment analysis. the

sentiment score is figured out for the sample of tweets.

Month on month growth of tweets, followers and following is calculated then based on the

result of Semantria tool sentiment score positive, neutral and negative score is published

which shows how people have reacted to particular phase or over a period of time..

Then an analysis of common words (for eg. love, accept, challenge, disease etc. ) which had

been figured out most in all the tweets has been taken out. These words depending upon their

presence in phrases signifies the likes, following, follower of tweets which help in making

connections and simultaneously helped in making ALS viral.

Next step was to separate out phrases which consisted of words like challenge, accept and

donation. Group phrases together under the heading of challenge, accept and donation and

find out sentiments for all three to figure out the reactions and trends.

As a result of sentiment analysis it is quite evident that few words (positive or negative) in a

phrase make connections, strong reactions and help in making video viral. However the scope

of study is limited to the number of tweets available. People have accepted the challenge and

thrown a challenge to an opponent wholeheartedly which helped numerous people to

participate in challenge and hence tweeting once accepting, donating and challenging ALS

Ice bucket challenge.

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FINDINGS