Making big data analysis more credible

Tengjiao WANG; Xilian LI

doi:10.11959/j.issn.2096-0271.2017017

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Making big data analysis more credible

TOPIC:BIG DATA MANAGEMENT AND ANALYTICS | 更新时间：2024-06-03

- Making big data analysis more credible
- Big data research Vol. 3, Issue 2, Pages: 2017017(2017)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2017017
  CLC： TP391
- Online First：2017-03，
  
  Published：20 March 2017
- 稿件说明：
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Tengjiao WANG, Xilian LI. Making big data analysis more credible[J]. Big data research, 2017, 3(2): 2017017.
DOI：

Tengjiao WANG, Xilian LI. Making big data analysis more credible[J]. Big data research, 2017, 3(2): 2017017. DOI： 10.11959/j.issn.2096-0271.2017017.

摘要

大数据在学术界和产业界的各个领域正扮演着愈加重要的角色，但同时，大数据是否可信，引发了无数研究者的广泛关注和激烈讨论。从大数据名称的历史演变、大数据应用的案例分析以及大数据工程的角度探索大数据的可信程度，并由此总结出保证大数据分析正确性需要解决的3个挑战：正确选择数据源、科学抽样有代表性和有价值的数据、严谨完备的大数据工程分析方法。

Abstract

Big data is playing an increasingly important role in various areas of academia and industry.However，whether big data can be trusted has caused widespread concern and intense discussion among countless researchers.The credibility of big data from the historical evolution of big data names，case studies of big data applications and big data engineering was explored，and thus the three challenges needed to be addressed to ensure the correctness of big data analysis were concluded:the right choice of data source，the scientific sampling of representative and valuable data，the rigorous and complete big data engineering analysis method.

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references

BOND R M ， FARISS C J ， JONES J J ， et al . A 61-million-person experiment in social influence and political mobilization [J ] . Nature ， 2012 ， 489 ( 7415 ): 295 - 298 .

EINAV L ， LEVIN J . Economics in the age of big data [J ] . Science ， 2014 ， 346 ( 6210 ):1243089.

SCHICH M ， SONG C ， AHN Y Y ， et al . Anetwork framework of cultural history [J ] . Science ， 2014 ， 345 ( 6196 ): 558 - 562 .

KHOURY M J ， IOANNIDIS J P A . Big data meets public health [J ] . Science ， 2014 ， 346 ( 6213 ): 1054 - 1055 .

CURTIN R ， PRESSER S ， SINGER E . Changes in telephone survey nonresponse over the past quarter century [J ] . Public Opinion Quarterly ， 2005 ， 69 ( 1 ): 87 - 98 .

WEISBERG H F . The total survey error approach:a guide to the new science of survey research [M ] . Chicago : University of Chicago PressPress ， 2005 .

CROSAS M ， KING G ， HONAKER J ， et al . Automating open science for big data [J ] . The Annals of the American Academy of Political and Social Science ， 2015 ， 659 ( 1 ): 260 - 273 .

KING G . Ensuring the data-rich future of the social sciences [J ] . Science ， 2011 ， 331 ( 6018 ): 719 - 721 .

ASUR S ， HUBERMAN B A . Predicting the future with social media [C ] // 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)，Aug 31-Sept 3，2010，Toronto，Canada . New Jersey : IEEE Press ， 2010 ： 492 - 499 .

CONNOR B O ， BALASUBRAMANYAN R ， ROUTLEDGE B R ， et al . From tweets to polls:linking text sentiment to public opinion time series [C ] // 4th Int'l AAAI Conference on Weblogs and Social Media，May 23-26，2010，Washington，DC ， USA .[S.l.:s.n. ] 2010 .

GOLDER S A ， MACY M W . Digital footprints:opportunities and challenges for online social research [J ] . Annual Review of Sociology ， 2014 ， 40 ( 1 ): 129 - 152 .

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