How to use "Long tail effect" in social media

In statistics, most random data are presented as a normal distribution with a middle high and two low. This characteristic applies to the Internet information flow, is the public hot spot the message is at the high end of all information, but the smaller obscure information is located at the bottom of all information.

The first question is, are these small and obscure messages valuable?

The question is not difficult to answer. The market's "28" theory shows that 80% of the total market revenue from the market share of 20% of the hot products, therefore, in the pursuit of profit maximization of economic interests driven by more enterprises in the past to focus on demand-selling products, ignoring unsalable products, the result formed a normal curve between the head of the "Red Sea" of the excessive competition, But to the broader "blue sea" market has overlooked suspicion. Since the "Long Tail theory" came out in 2004, more and more industries in the field of economy have noticed the concern of the market "blue sea".

Long tail in normal distribution (market blue ocean)

In the internet age, Amazon's online bookstore and Google search were seen as the best practitioners of the theory. A former Amazon employee has brilliantly outlined the "long tail" nature of the company: the books we sell in the past are much more than the ones we sell that used to sell. Google AdSense allows tens of millions of small businesses and individuals to be able to advertise at low prices, and allow many sites and personal sites can easily become an advertising platform to profit from it.

For social media and social media, the long tail effect has become a more and more worthwhile research topic. This is because, on the one hand, social media and social media promote the explosive development of content and interpersonal relationships, make oneself already become a rich information platform, this platform of information active degree must exist a very spectacular normal distribution curve, this spectacular normal distribution curve determines it can effectively use "long tail effect On the other hand, its information explosion has also led to a serious problem of overload, the accumulation of miscellaneous data and hot information has hindered the dissemination of some original but relatively small information content.

So the second, and more important, question is how to fully expand the ability of these small-audience information to produce a more valuable mass of information?

In order to improve the effective reading of information, avoid information congestion, but also improve the "long tail effect," social media, social media and some third-party applications are also groping for a certain solution:

Social media:

1) subdivision of content, resulting in more detailed classification information aggregation.

Some social media, represented by light blog, will target the market clearly in the distribution of information, specifically targeted at the blue Ocean for the distribution of information to expand.

To Tumblr, Dot network, such as light blog for the representative, widely used information classification more vague, random label classification and recommendation mode, this kind of label recommendation can be to a certain extent effectively improve the spread of minority content and aggregation. At the same time, the recommendation of the label is not fixed, the content is constantly changing, so that the label of the minority information can also be promoted to spread the opportunity.

A lightweight blog that uses labels to classify

2 more conducive to reading content presentation.

or on behalf of the light blog, content is not presented as a micro-blog and social media information dynamic short mode, but the image is magnified, the default rendering more words, so that the layout is more close to the full text of the reading form and habits, so that users can browse information more focused.

On the other hand, this richer content information also means that the information provider to increase the difficulty of information manufacturing, so can reduce the number of information to a certain extent, so as to improve the possibility of "long tail effect."

3 Add random referrals based on user relationships or interest.

Although there is no social media to explicitly launch this function. The most recent function is Weibo "grab sofa" game, and then this game is only suitable for some microblogging novice, in the initial expansion of the user relationship can also have a certain role, however, in the micro-Bo users in the current large-scale development, this function is reduced to chicken.

Micro bo Rob sofa function: Can randomly find an unpublished Weibo

One of the things you can do is to add random content recommendations to your friends and topics of interest. The image on the right is the Sina Weibo new version of the hot Comment recommendation bar, the current column is only recommended some focus on the user's hot information, if you can for the non-hot information also carry out a certain random recommendation, then it can be said to achieve a certain "long tail effect" to promote the role.

4 Localized content segmentation.

At present, Sina Weibo in the Micro-topic aggregation page has a "regional hotspot" category, this classification is a number of local hot event aggregation. The aggregation of these regional hot events is a further subdivision of the content, which is beneficial to the realization of "long tail effect". However, it is regrettable that the current idea of content segmentation based on the region does not appear on the right side of the microblog. It would be a good practice to use the "long tail effect" If you can add a random recommendation of local content to the sidebar of a Weibo personal page.

Regional Hot Topics

Social media:

1 Stripping system dynamic and original information.

An important way to enlarge the "long tail effect" is to reduce redundant information, especially to peel away the system information and original information. Social media such as "like", "support" and other social buttons to provide users with the convenience of creating information, at the same time, social media applications in the user dynamics has generated a large number of system dynamic information. This information on the one hand is to create hot information, improve interpersonal interaction of powerful hands, but it is this information, the user a large number of original information has been buried.

Facebook unveiled a number of new features and online programs at the Facbook Annual developer conference--F8 meeting on September 22. On the one hand is the most noticeable timeline function, will individual important activities and achievements in the timeline, stripping miscellaneous information, highlighting important information dynamic. On the other hand, Facebook unveiled the new information area ticker at the F8 conference.

Facebook New Sidebar Ticker

Facebook Split the system dynamic information from the "Dynamic Rollup" area of the original user's friends into ticker and added real-time dynamic information to the ticker. This is considered to be the most important update for Facebook after timeline. Although the inclusion of real-time dynamic is considered to have privacy risk, but stripped of the system dynamic main content area "Dynamic Summary" is obviously more "clean", on the basis of the information content is also easier to obtain "long tail effect."

2 focus on the content of the information reading mode.

Another new service that Facebook unveiled at the F8 conference is NewsFeed, a service that is not hard to understand, aimed at introducing more news and media content so that users can read the full newspaper and magazine articles without Facebook. But this is not the focus of this article, the focus is that newsfeed provides a more able to enable users to focus on the layout of the way, a single piece of information more pictures, so you can achieve a similar light blog focus on reading effect.

More noteworthy is that the scope of this reading will be further expanded, not only the traditional news, media content providers. Facebook's new open Graph feature allows all users who are free to join developers to build their own reading information, and in the future, Newsfeed's reading model will become more common on Facebook.

3 According to the user on-line status of different information recommended mode.

Facebook's new News Feed information flow service organically integrates "important information" with "the latest". The feature of the Integrated information flow service is that if users log on to Facebook very frequently every day and log on many times a day, most of the information that users see in the stream is "the latest"; If users log on to Facebook at a very low frequency, Most of the information that users see in the stream is "important information" these days.

This approach has been close to using the long tail effect. The next step for Facebook is to provide a more random, more interesting stream of content to users of different online statuses, so the newsfeed can fully implement the "long tail effect".

Third-party applications:

The two main ways that third-party applications currently provide social media and social media with a "long tail effect" are:

1, the focus of reading mode;

After the famous Flipboard caused sensation, the mobile platform feeds the application to read unceasingly. Flipboard can import your Twitter and Facebook accounts, making social media and social media content a reading model for magazines. Dolphin browsers on the domestic mobile platform also add reading patterns to Web browsing, making it possible for Web pages, including social media and social media, to focus on reading. These dedicated reading applications will undoubtedly make social media and social media information reading more clearly and efficiently, so that some of the past difficult to read the content of the discovery and attention, and effectively enhance the "long tail effect."

Flipboard easily turn social media and social media into reading magazines

Third-party classification information platform.

A growing number of third-party applications on Facebook, Renren and Sina have also partly achieved a diversion of information. For example, micro-blogging platform's "micro-activities", "micro-recruitment", "Micro-program", into these activities to share and view friends information than from the micro-blog to see more focus on the flow. But these are only limited to the extent of the "long tail effect" of the application, or not fundamentally solve the information flow and effective recommendation of the problem, from this point of view, still need a can be based on information content to classify the application or tool.

Summary of the application method of "long Tail effect":

Social media and social media "long tail effect" of the use of the method currently has four main aspects.

-More detailed and interesting subdivision of content.

-Content recommendation. Includes low level random recommendations, and algorithms based on interest, personalized recommendations.

-Peel off "cheap information". Let the system dynamic information and forwarding this "cheap" production of information from ordinary information stripped.

-a focused reading model. Simplify redundant information, enlarge reading information, and enable users to read more efficiently.