About a month ago, I wrote about大約一個月前，我寫 patterns I found comparing Yale and Harvard in Google searches through Google Trends模式我發現比較，耶魯和哈佛在Google搜索通過Google趨勢 . 。 Well, just today, Facebook released a simply fascinating tool called “那麼，就在今天， Facebook已經發表了一份簡單有趣的工具，所謂" Lexicon詞彙 ” which is the same thing, but for wall posts. " ，這是同一回事，但對牆體的職位。 Computers (not humans!) track the content of every wallpost for words and phrases, and you can search for trends and comparisons over time using this new tool.電腦（不是人類！ ）軌道的內容，每wallpost單詞和短語，你可以搜尋趨勢和比較，在一段時間內使用這一新工具。 Very cool, right?很冷靜，對不對？

Lexicon shows the number of users that posted each term per day on a profile, event or group Wall.詞庫顯示有多少用戶張貼每屆任期內每天概況，事件或一組牆。 It does not count repeated terms by the same user on the same day.它不指望得到反复計算，由同一個用戶在同一天。 This is to account for the seasonality of Wall posting in general; for example, there are fewer overall posts in the month of December.這是佔了季節性的牆上張貼在一般;舉例說，有少，整體職位在12月份。

My complaint about my previous Google Trends related efforts had been the fact that Google Trends was not targeted enough to college age students to give more precise sampling to *really* show the trends when it came to buzz about individual schools over the course of the admissions cycle.我的投訴說，我以前的Google趨勢相關的努力一直是一個事實，即Google趨勢，是不是有針對性不夠大學年齡的學生給予更精確的採樣，以*真的*顯示趨勢的時候，它來到buzz關於個別學校在課程招生循環。 Facebook’s demographics pretty much fix this problem, and the following chart is very exciting. Facebook的人口統計數據都很解決這個問題，請與下列圖表，是非常令人興奮。

The greatest influence here can be seen from Harvard and Princeton dropping their early programs.最大的影響力在這裡可以看到來自哈佛大學和普林斯頓下降，其早期節目。 Yale has a huge attention buzz boost in December, but by spring admissions time it is at parity with Princeton (Gasp!) and Harvard has a significant edge in attention.耶魯大學有一支龐大的注意分類推動去年12月，但由春季招生的時候，它正處於同等地位與普林斯頓（讚歎！ ）和哈佛大學有一個顯著的優勢，在注意。 As with Google Trends data, the same incredibly eerie trend occurs where everyone talking about school A talks exactly proportionately with those talking about school B with the same upticks and downticks, with high levels of accuracy.作為與Google趨勢的數據，同樣令人難以置信的怪誕的趨勢出現，每個人都談論學校的會談正是在比例上與那些談論乙校與上年upticks和downticks ，以高層次的準確度。

In general, the same observations as before apply… just nice to see them borne out in slightly cleaner data somewhere else.一般來說，相同意見之前，申請…剛剛尼斯看到他們證明，在稍微清潔數據在其他地方。 Read about the patterns I found in the Google Trends data by clicking閱讀關於模式我發現，在Google趨勢的數據通過點擊 here這裡 , or see below.或見下文。

Compare with比較 Google Trends data Google趨勢的數據 (Red is Harvard, blue is Yale). （紅色是哈佛，藍色是耶魯大學） 。