追求人們之需求，提高建築環境的舒適度和經濟使用率為當今社會之目標，也由於現今人口出生和衰老之影響，社會人口結構發生了變化，人類之用電行為也產生了改變。隨著世界持續城市化，都市人口密度逐漸增長，建築設施也大幅度之增加，近年來，節能問題於今日之碳減排趨勢中變得越來越重要，就建築物而言，以一般住宅型態與商業型態之建築物為能源消耗之主要指標，因此，本研究將基於人類用電習慣之因素，探索一般住宅類型建築物之能源消耗，憑藉所提出之加權傳播設計與屬性資料建構，搭配關鍵因子之分群規則進一步創建社交網絡分析模型，除了透明化住戶用電之使用模式，更於社群中找尋具有較高影響力之關鍵人物，進而有效傳遞節能訊息，透過資訊之交流，供其他人學習與效仿，降低民眾之用電額度，達到節能減碳之效果。

Reducing carbon footprints in the building sector can be achieved by altering the power consumption behavior of building residents. Due to the influence of today’s declining birth rate and population aging, the structure of human society is changed, requiring the identification of key persons active in a community to persuade the others into saving electricity. This research aims at applying the technique of social network analysis (SNA) to a publicly available smart meter data set for building residents in Germany. Traditionally the head of a community can serve as the role of broadcasting energy-saving information, although its effectiveness varies with different circumstances. In the proposed SNA-based approach, the German data set is firstly examined and pre-processed, such as augmenting building occupancy data and relationships among residents. Then, different SNA indexes are explored in order to derive a generalized procedure for such identification of key persons. More sustainable societies can be established if key persons of a community can be identified and get involved by using the proposed approach. Energy-saving information specific to each type of home appliance can be broadcast effectively and efficiently, based on such identification, so that all building residents can implement the corresponding energy saving tips.

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