????社交共享是由公司集中控制的。瀏覽量是一個用以衡量開放網絡，可以通過各種手段進行跟蹤的量化標準。而社交共享則是由社交網絡自身集中衡量，并向外發布的。社交網絡可能存在寬松地計算共享數據以顯得自身更受歡迎的動機，盡管出版商可以核實這些共享數據是否真正帶來了頁面流量。這當然是一個問題，它從屬于一個更大的憂慮：許多人擔心互聯網本身是不是正在變得更加集中化。

????社交共享是一個大混雜。一個與上述批評意見相關的問題是，什么數據可以納入社交共享指標，可能會因為社交網絡自身的不同想法而瞬息變化。計算社交共享時往往出現一些我們可能并不認同的主觀判斷，比如把一條鏈接微博的轉發也算作一次社交共享。當然，確定瀏覽量或者谷歌分析（Google Analytics）和Omniture提供的獨立訪問量服務時，同樣也存在大量的主觀判斷。所以說，這種意見并不是什么新鮮事。但由于每家社交網絡皆是其社交共享數據的獨家提供商，這種憂慮的確出現了增大的趨勢。

????自動分享增加了社交共享數值。有些Twitter賬戶的創建目的就是為了發布一些給定的RSS訂閱源，所以有些文章不管質量如何，總會在Twitter上獲得不少分享次數。這種情況肯定將扭曲社交共享數值，但由于Twitter留言是公開的（不計算來自私人Twitter賬戶的留言），這種情況一旦出現，是可以被檢測到的。

????我們已經把所有的反對意見都擺放在臺面上了，接下來讓我們總結一下社交共享的優點：

????社交共享是一種有意圖的用戶行為。一個誤導性標題、一張預覽照片或一個搜索結果常常會很容易地慫恿我們瀏覽一篇我們其實不想閱讀的文章。如此以來，我們就為出版商的瀏覽量和收入做出了貢獻。但正如Buzzfeed公司負責產品事務的副總裁克里斯?約翰內森所言：“你無法哄騙某個人向他或她的朋友分享一篇文章。”在社交媒體分享一篇文章，是一種意圖非常明顯的用戶行為，需要比一次瀏覽量更多的點擊次數。

????社交共享關乎用戶的社交網絡形象。與瀏覽量和評論不同，人們非常用心地分享一篇文章，意味著他們愿意在Twitter上告訴整個世界或者至少告訴Facebook上的朋友，他們喜歡這篇文章。

????社交共享不依賴抽樣。在如今的網絡上，來自尼爾森公司（Nielsen）和康姆斯科公司（comScore）的抽樣數據是少數幾個相對客觀的關注度衡量指標之一。做得好時，采樣可以成為一個強大的指標。但正如許多宣稱選舉不公道的人士所知道的那樣，這種做法并不完美。少數派和新平臺經常未被充分代表。由于缺乏數據，采樣數據只能顯示某個出版物層級，而不是一篇給定文章的受關注度。與之相比，社交共享數據能夠充分顯示網絡上每篇文章的分享次數。

????社交共享次數是公開的，因此不易造假。不同于其他任何網絡衡量標準，任何人都可以看到社交共享次數。眾所周知的是，許多出版商和企業家都在操縱他們向公眾發布的指標。他們往往能夠逃脫懲罰，因為只有他們擁有分析系統的訪問權限。而社交共享則不在出版商的掌控范圍，它是一個統一的尺度。

????Social shares are centrally controlled by corporations. While pageviews are a measure of the open web that can be tracked through a variety of means, social shares are centrally measured and reported by the social networks themselves. There may be an incentive for the networks to count these numbers liberally to appear more popular, though publishers can check if it's actually resulting in traffic. This is certainly a concern, and a subset of a larger worry many have about the web being more centralized in general.

????The definition of a social share is influx. Related to the prior criticism, what goes into the social share metric can change at the whim of a social network. There are judgment calls that go into calculating what a social share is, such as counting retweets of a tweet with a link as a share itself, we might not agree with. Of course, there are plenty of judgement calls that go into defining a pageview or unique visitor by services like Google Analytics (GOOG) or Omniture (ADBE), so this is nothing new. But the concern is heightened since each social network is the exclusive provider of its own share counts.

????Autosharing increases social share counts. There are some Twitter accounts set up to tweet anything in a given RSS feed, so some articles will get a handful of tweets no matter what. When this happens it definitely skews the numbers, but since tweets are public (tweets from private Twitter accounts are not counted) it can be detected when this occurs.

????Now that we've got the objections on the table, let's look at the virtues of social shares:

????Social shares are an intentional action by users. It's easy to get pulled into viewing an article you don't really want to read by a misleading headline, preview photo or search result, which results in a pageview and often revenue for the publisher. But as Buzzfeed's VP Product Chris Johanesen wrote "you can't trick someone into sharing a story with their friends." Sharing an article on social media is a very intentional act by a user, requiring several more clicks than a pageview.

????Social shares require users to put their identities on the line. Unlike pageviews and comments, when people care to share an article they're willing to tell the world on Twitter or at least their friends on Facebook (FB) that they care about the article.

????Social share counts don't rely on sampling. One of the few objective measures of attention on the web today is sampled data from the likes of Nielsen (NLSN) and comScore (SCOR). When done well, sampling can be a powerful indicator, but as many people who've miscalled elections know it's not perfect. Often minorities and new platforms are underrepresented. Sampled data can only be reported at a publication level rather than for a given article due to lack of data. Social share numbers report a full count for every article on the web.

????Social share counts are public and therefore not easy to fib about. Unlike just about every other web metric, anyone can look up social share counts. Many publishers and entrepreneurs are known to manipulate the metrics they release to the public. They've been able to get away it with since only they have access to the analytics system. Social shares are out of the control of the publishers and a uniform metric.