BANGALORE, March 22, 2013 /PRNewswire/ --
Big Data Analysis Reveals Social Performance of the Indian Players During the Border-Gavaskar Test Series
Master Blaster Sachin Tendulkar continues to rule the game of cricket even across social networks, followed by captain Mahendra Singh Dhoni and opening batsman Murali Vijay. This is as per IBM's Social Sentiment Index announced on the eve of the last test match in the the ongoing Border-Gavaskar cricket series between India and Australia. Ravindra Jadeja's exceptional performance in the series makes him the most popular bowler in the Indian team.
A real time analysis on social sentiment of cricket fans and alike conducted by IBM during the first three matches shows that cricketing legend Sachin Tendulkar consistently leads the overall conversation in this period. 50% of the public sentiment revolved around his batting performance followed by his past records, his stature and retirement plans, among others.
The index further revealed that negative sentiment towards Captain Dhoni was high at the beginning of the first match. However, his on field performance is reflective of how public sentiments changed, making Dhoni the most positively referenced player in the series. Another interesting highlight was the emergence of Shikhar Dhawan on the social networks after his debut century - within 5 days, there was 200% growth in his online conversations.
For the first time, IBM applied advanced analytics software and natural language processing to cricket to build a social score board for the Indian Players based on the intensity of the sentiment and volume of online conversations. Over 1.2 lakh posts across a variety of platforms including Facebook, Twitter, YouTube and the blogging community were analysed during the first three matches in the current series.
Speaking about IBM's Social Sentiment Index, Virginia Sharma, Vice President - Marketing & Communication, IBM India/South Asia, said, "Today, IBM is changing the game - both in business and in sports. By applying the social sentiment lens to cricket that has a multi-screen experience, we demonstrated how analytics can provide real time exciting insights into public preferences. This can be leveraged by organizations across the media, entertainment and sports industries to better understand their audience, determine endorsement values, and deliver effective marketing campaigns for their businesses."
A closer look at the results generated by the IBM's social sentiment index for the cricket Test series reveals some interesting facts about the game off the pitch:
- With a 3-0 lead, the positive sentiment for the Indian team has been steadily on the rise.
- Pitches, spinners and player selection continued to be the hottest topic of conversations.
- Though Ravichandran Ashwin has bagged the highest number of wickets in the last three games, it was Ravindra Jadeja followed by Harbhajan Singh who came up on top of the social score-board for the bowlers.
- Jadeja's 17-wicket haul helped him increase the social conversations by 7 fold after the first two Test matches.
- The Turbanator may not have had a good series and got dropped in the third Test, but Harbhajan Singh ruled the social networks with 36% more conversation than the best spinner on field (Ashwin).
- Murali Vijay, who is the third batsman as per the social score, saw a consistent rise in his social chatter by an average of 160% between the first and third Test - a clear reflection of his consistent performance on the pitch.
- Majority of the conversation for Vijay centered on his batting performances - poor score in the opening test, record partnership with Pujara, etc.
- While Shikhar Dhawan and Murali Vijay batted for a record partnership, on the social arena, the debutant became the most talked about youngster in the Indian cricket squad in just 4 days.
- Indian batsmen definitely proved more popular across social networks than the bowlers.
For more interesting insights, please refer to the infographics here http://bit.ly/1026Djn
About the IBM Social Sentiment Index
The IBM Social Sentiment Index uses advanced analytics and natural language processing technologies to analyze large volumes of social media data in order to assess public opinions. The Index can identify and measure positive, negative and neutral sentiments shared in public forums such as Twitter, blogs, message boards and other social media, and provide quick insights into consumer conversations about issues, products and services. Representing a new form of market research, social sentiment analyses offer organizations new insights into Big Data that can help them better understand and respond to consumer trends. For more information about IBM please visit: www.ibm.com/social-sentiment.
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SOURCE IBM India