The prediction of petition based on Big Data
| Date | 19 August 2019 |
| DOI | https://doi.org/10.1108/IDD-08-2018-0031 |
| Pages | 135-142 |
| Published date | 19 August 2019 |
| Author | Ting Xue,Huiqi Liu |
| Subject Matter | Library & information science,Library & information services,Lending,Document delivery,Collection building & management,Stock revision,Consortia |
The prediction of petition based on Big Data
Ting Xue and Huiqi Liu
Tianjin University of Traditional Chinese Medicine, Tianjin, China
Abstract
Purpose –The development of Big Data and online searching engine provides a good opportunity for studying petition in China. This study has
constructed a set of indices for predicting petitions in China by using online searching engines and further explored the predicting role of economic,
environment and public life risk perception in various petitions.
Design/methodology/approach –Based on the study of Xue and Liu (2017), this research first re-classified offline petition by human and cluster
analysis in terms of social risk perception and built online searching indices of the two sets of petition by using data from “Google Trend”and
“Baidu Index.”Second, it analyzed the predicting effect of social risk perception on online searching indices of petition by using Granger causality
analysis. Finally, this study integrated the results and selected significant paths from social risk perception to the two sets of petition.
Findings –The study found that the re-classification made by human was more appropriate than the categories made by cluster analysis in terms of
social risk perception. For the two sets of petition, the correlations between offline petition and Baidu Index of petition were both more significant
than that of Google index. Moreover, economic and finance and resource and environment risk perception had a significant predicting effect on
more than one kind of online searching indices of petition.
Originality/value –The results have demonstrated the important role of economic issues in China on predicting petitions of the economic kind, as
well as other kinds. They have also reflected the dominant social contradictions and their relationship in modern China.
Keywords China, Big Data, Baidu Index, Google Trend, Petition, Social risk perception
Paper type Research paper
1. Introduction
It has been realized that the development of the internet, mobile
communication technology and cloud computing has prompted
the accumulation of data and the advent of the new era of Big
Data. Big Data is a relatively abstract concept that mainly refers
to the huge amount of complex data which is difficult to obtain,
store, manage and analyze using normal database software
(Manyika et al.,2011). The development of Big Data
demonstrates that everything can be digitized, the whole is
greater than the sum of parts and data can have a powerful
predictive function. These characteristics have triggered the
revolution of various disciplines in research technology and
research content (Chen, 2016).With respect to social science, Big
Data has several excellent advantages, compared with traditional
questionnaire and experiment, such as timeless and effortless,
more natural and real and sample-rich (Xue and Chen, 2015).
Therefore, researchers have attempted to integrate data from
multiple different sources and to uncover the prediction fu nction
embedded in these data. The ideal sources are the ones which
can maximally reflect the real life and can be used conveniently
(Chen, 2016). Because a huge number of people have been using
the Web searching engines to search for information of interest,
searching engines, as an important database in indicating
people’s mind and behavior, have of course drawn much
attention in various areas (Kristoufek, 2013).
One of the most famous Web searching toolsis Google, who
has developed Google Trends (www.google.com/trends/)to
provide a relative search volume of certain terms searched in
Google search engine at a given time (Kang, et al., 2013;
Mellon, 2014;Vaughan and Chen, 2015). GoogleTrends has
been widely used in Western countries to manifest the salient
issues and the public opinion (Nuti et al., 2014) or to predict
offline events such as regional disease (Kang et al.,2013),
trading volume and stock indices (Shen et al.,2017). Baidu
Index (http://index.baidu.com/) is the counterpart of Google
Trends in China. It offers an absolute searching number of
certain terms queried at www.baidu.com. As Baidu is the
biggest Chinese searching engine and has much more users
than Google and other enginesin China (Wang and Jia, 2014),
researchers began to use Baidu Index, or both Google Trend
and Baidu Index, to predict diseases (Hutzler and Linton,
2012;Li et al., 2017), business cycle states (Chen et al., 2015)
and stock prices (Shen et al.,2017).A study has found that data
concerning certainChinese issues from both Google Trend and
Baidu Index were highly correlated and the combinationof the
two volumes did not make a differencein the predictive power
(Vaughan and Chen, 2015), indicating the high reliability of
Baidu Index in the Chinese context.
2. Literature review
In social science, collective action is always a difficult issue for
traditional researching methodsto study. Petition in China is a
typical example. It has been discussed that Chinese people
The current issue and full text archive of this journal is available on
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Information Discovery and Delivery
47/3 (2019) 135–142
© Emerald Publishing Limited [ISSN 2398-6247]
[DOI 10.1108/IDD-08-2018-0031]
Received 17 August 2018
Revised 11 September 2018
1 October 2018
22 October 2018
Accepted 1 November 2018
135
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