Look at the social trends of big data from Twitter messages
Source: Internet
Author: User
KeywordsLarge data large data messages large data messages trends large data messages trends social large data messages trends social attention
The research and analysis of Twitter suggests that interest in big data has grown rapidly in 2012 years, but in fact there is more to it than the statistics on Twitter messages, which in itself are a "big data".
In April of this year, a number of conferences or events with large data themes were held around the world, including http://www.aliyun.com/zixun/aggregation/13527.html ">big data week activities, Social media-related activities like this seem to be growing. DataSift is a large data service provider, which often tracks dynamic information about meetings and forums, and DataSift's best job is to predict future trends by analyzing the content of Twitter messages. Recently, Tim Barker, from DataSift, provided an information graph showing some of the new discoveries made by DataSift after studying a number of Twitter messages in 2012, which contain the keyword "Big data".
One of the main points of information in the analysis is that the world is still learning and understanding big data, which is likely to mean that we are in the early adopters of large data rather than at the peak of the hype phase. The following is a brief description of some of the analysis data:
· The number of Twitter messages on big data was almost unchanged in the first two quarters of 2012 years, while the two-quarter increase was 25%;
· 72% of the content includes web site links to the Twitter message, indicating that these conversations are mainly about information resource sharing issues;
· Most of the articles that were shared in the 2012 were the interpretation and exploration of the theme of "revealing myths";
· Because of Hadoop, Apache is the most frequently mentioned product, but MongoDB developer 10gen is definitely a very competitive runner;
· IBM's dynamic content marketing strategy has certainly helped it beat Hewlett-Packard, Core, Oracle and EMC in the number of keyword mentions;
· Splunk's initial public offerings raise its profile. HP, on the other hand, gets the most negative message about big data because it is caught in the autonomy of the incident.
· Japanese users have a preference for private solutions, which makes Cloudera more than any other competitor in the market;
· Splunk is the most watched in the United States, DataSift is the most concerned in the UK, SAP is the most concerned in Germany, IBM in France is the most concerned.
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