本研究欲了解染料敏化太陽能電池的學術文獻發展的過程以及有哪些文獻是有
顯著貢獻的。因為這門學問的文章數量十分龐大,想要透過人工的方式了解整個學
問的發展結構以及那些文獻是對此科技有重要貢獻十分不容易。剛進此領域的研究
學者,不容易掌握整個研究的概觀發展也不容易找到重要的文獻,大多要透過他人
的推薦。
本研究透過主路徑分析套用在引文網路的關係,嘗試驗證此方法是否能夠從染
料敏化太陽能電池的文獻集合中篩選出重要的文獻,並提供宏觀的發展結構。由於
既往的主路徑分析的分析對象大多只有一千多筆的資料,本實驗首次嘗試數千筆資
料,能提供後人分析時的參考經驗。另外,針對過去既有的主路徑分析方法,本實
驗嘗試去除回顧文獻,評估這樣的做法是否可以讓結果更精確更接近事實。
實驗結果告訴我們染料敏化太陽能電池的發展歷程,在不同的年代區間有不同
的研究重點,也會伴隨不同程度的創新發展數量,每條的路徑都可能是一條不同的
發展重點。為了使大量資料的收集更為精準,本研究改良關鍵字的搜尋邏輯,欲使
資料集合中的垃圾文獻降到最低,避免影響結果的準確性。在分析軟體方面也將出
現迴圈的現象改良,大幅度減省分析的時間。
在排除回顧文獻方面,排除之前的複雜度很高,很難看出端倪,在排除之後發
現可以明顯改善這樣的現象;同時也發現,重要的學術文獻在新的分析結果中還是
不會改變。
實驗的結果可以提供剛開始研究染料敏化太陽能電池的學者一個參考的依據之
外,更重要的是本實驗在研究大筆資料的經驗可以提供未來學者在面對此類研究對
象時有效的建議。

We tried to know what is about the progress of the DSSC (dye-senstied solar cell) papers and which are the more imprtant among them. Due to the huge size of the data, it would be a complex issue to find out the comparely more important paper or the whole progress for the beginer in this field.
We focus on analysising DSSC by mainpath analysis ,tried to fix the problem with the big data and see if we can figure out the whole picture and most importat papers of DSSC. In the past, we only analyse under 2,000 nodes with main path analysis. This very first time, we try to analyse with over 6,000 papers and had some experiece to share. Also, we compare the main path with and without the reivew papers catagolry and evaluate if it’s valueable.
The result tell us the progress of DSSC with different time range, also we prove that excluding the review paper may improve the result and provide a clearer main path. For collacting more presice data, we also improve the logic of key-words and prevent from any junk date coming.
We also found that take out the review paper helps the main path picture less complex and easier to understand the progress of the developement.We believe this reserch could not only help beginer understand more about DSSC, but provide the experience of analysing big data.

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