Reality Mining: Using Big Data to Engineer a Better World (Hardcover)
暫譯: 現實挖掘:利用大數據打造更美好的世界 (精裝版)
Nathan Eagle, Kate Greene
- 出版商: MIT
- 出版日期: 2014-08-01
- 售價: $880
- 貴賓價: 9.5 折 $836
- 語言: 英文
- 頁數: 208
- 裝訂: Hardcover
- ISBN: 0262027682
- ISBN-13: 9780262027687
-
相關分類:
大數據 Big-data
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相關主題
商品描述
Big Data is made up of lots of little data: numbers entered into cell phones, addresses entered into GPS devices, visits to websites, online purchases, ATM transactions, and any other activity that leaves a digital trail. Although the abuse of Big Data -- surveillance, spying, hacking -- has made headlines, it shouldn't overshadow the abundant positive applications of Big Data. In Reality Mining, Nathan Eagle and Kate Greene cut through the hype and the headlines to explore the positive potential of Big Data, showing the ways in which the analysis of Big Data ("Reality Mining") can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy.
Eagle, a recognized expert in the field, and Greene, an experienced technology journalist, describe Reality Mining at five different levels: the individual, the neighborhood and organization, the city, the nation, and the world. For each level, they first offer a nontechnical explanation of data collection methods and then describe applications and systems that have been or could be built. These include a mobile app that helps smokers quit smoking; a workplace "knowledge system"; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and the analysis of social media to track the spread of disease. Eagle and Greene argue that Big Data, used respectfully and responsibly, can help people live better, healthier, and happier lives.
商品描述(中文翻譯)
大數據是由許多小數據組成的:輸入手機的數字、輸入GPS設備的地址、訪問網站、在線購物、ATM交易,以及任何留下數位痕跡的活動。儘管大數據的濫用——監控、間諜行為、駭客攻擊——已經成為頭條新聞,但這不應該掩蓋大數據的豐富正面應用。在《現實挖掘》(Reality Mining)一書中,Nathan Eagle和Kate Greene突破了炒作和新聞標題,探索大數據的正面潛力,展示了大數據分析(“現實挖掘”)如何用於改善各種人類系統,如政治民調和疾病追蹤,同時考慮用戶隱私。
Eagle是一位公認的領域專家,而Greene則是一位經驗豐富的科技記者,他們從五個不同層面描述了現實挖掘:個人、社區和組織、城市、國家以及世界。對於每個層面,他們首先提供了數據收集方法的非技術性解釋,然後描述已經建立或可能建立的應用和系統。這些包括幫助吸煙者戒煙的移動應用;一個工作場所的“知識系統”;利用GPS、Wi-Fi和手機數據來管理和預測交通流量;以及分析社交媒體以追蹤疾病的傳播。Eagle和Greene主張,尊重和負責任地使用大數據,可以幫助人們過上更好、更健康和更快樂的生活。
