Social Big Data Nuggets Road: The biggest obstacle to privacy issues

With the development of social networks entering the bottleneck period, the value of the user data generated is much greater than the platform itself. How these data and content flows can be turned into a topic that Facebook, Twitter, and other social networking sites are constantly considering.

Social data is a big gold mine, a social platform that believes it. With more and more advertisers, product makers and brand marketers eager to connect to the social networking world, the value of user data is emerging. Next, look at how the social platform itself and other data marketing companies have explored this treasure.

Social Data Nuggets Road

Social giants Facebook and Twitter started their nuggets in social data early.

The real value of a thing depends not only on what it has done, but also on what it can do. Today's Facebook is like a huge digital castle with just a good foundation, and after the stock market catastrophe, it is no longer urgent for Facebook to quickly turn user data into a tool to increase revenue. As for how it uses this data, perhaps we can find some clues from the following series of actions:

In May 2011, Facebook deepened its collaboration with Microsoft's Bing and began using Bing to deeply integrate Facebook's social database. For example, after you give a search request, Bing is no longer just using a separate floating panel to show what your friends "like" on Facebook, but will reorder search results directly based on "like."

By August 2012, Facebook was taking a big step forward in digging up the value of its users ' data, acquiring Threadsy, a social data analysis firm that had developed social analysis tools Swaylo. And that means Facebook is starting to hold the initiative to tap the value of user data.

Not only that, his CEO, Zuckerberg, said publicly at the TechCrunch Disrupt conference: "Facebook has a unique advantage in answering user questions." "It sparked a frenzy of media and industry speculation about its search engine, and he finally confirmed it as well." Launching a search is not an easy task, it needs to be based on having a large enough data base and a comprehensive structure of the data.

"The value of Facebook is that they have huge user data. The company will improve the search engine's results by connecting pages, content, and social content. Christophe Henner, social media manager at X-prime Group, a French network technology company, clearly points out the prerequisites for Facebook's foray into search. Zuckerberg also said that at present there are more than 1 billion queries per day on Facebook, and they have a dedicated team that will create tailor-made search engines for specific users.

Unlike the strong chain of relationships formed by Facebook users, the link between Twitter users is a weak chain of relationships, and it also emphasizes itself as a social media focus that focuses on news dissemination and topical content discussions. The user data sample generated on this platform may not have the obvious individual behavioral characteristics of Facebook, but it is also highly public information analysis.

Although the number of users is less than Facebook, many people think that Twitter's interest map is better than Facebook's social graph. The potential value of Twitter's user data is equally stunning. This can be seen from the astonishing use of Twitter social data, from social monitoring to medical applications, and even to tracking outbreaks. The contribution of Twitter user data to the actual value of these niche applications is undeniable.

In the mining of these user data, Twitter has also conducted a series of explorations. Not long ago, Twitter and Salesforce.com signed the Data Pipeline licensing agreement, so Salesforce access to all of the Twitter public data, which is also a signal of Twitter's social data and corporate applications directly docking.

Twitter has taken a real step in how to comb through massive amounts of data. Edwin Chen, the company's data scientist, said Twitter would like to try a new--spark of large data systems. Spark is an open source cluster computing system based on memory computing, which is designed to make data analysis faster. This approach will greatly enhance Twitter's data Analysis Services.

By filtering user ownership, placement, and related keywords, Twitter builds a series of customized customer data streams. For example, by filtering movie title, location, and mood tags, you can tell what the most popular movies are in cities like Los Angeles, New York and London. And according to the user's personal behavior description, you can even search for Japanese tourists in Canadian chemistry. If you combine social data with other financial data, you can even turn Twitter into a stock trading tool.

(Responsible editor: The good of the Legacy)