research question

What keywords appear more times in the papers?

question04 1 马来西亚华人华人马来西亚马来人民族关系认同文化认同中华文化宗教华人社会马华文化节日侨民教育马来亚联邦计划东南亚华人马来人和华人公民权华人资本制造业华人企业集团汉字侨务政府华人经济华文教育马华公会马来西亚政府心理健康华侨华人研究马来亚幸福指数19世纪亚洲金融风暴政治参与度英中关系演变原因合法性社会支持政治系统政治认同特点政治经济形势海上交通语言马赛克语言融合教义结构集体记忆国籍问题伊斯兰教劳动密集型产品巫统关系发展马来西亚华人幼教老师
Description Protocol Data

Description

Continuing with what we have found in the last question that none of results in academic area are from Baidu, we wanted to explore deeper into this field.

Thus, the first question we wanted to ask is what keywords appear more times in the papers about Malaysian Chinese if we look in not only in Google but also in Baidu to see if there is any connection between the results from two acdemic sites. In order to know it, we searched 20 papers in Baidu Scholar and 20 papers in Google Scholar with “Malaysian Chinese” and collected the keywords of each paper.

We chose pie chart to visualize the data. The number of keywords in papers from google acdemic is 61, and that from Baidu is 90. The circles in 2 colors refer to common keywords that appear in papers from both two acdemic sites. The size of circle refers to the number of the times that each keyword appears in papers .

We found out that the keywords appear in both acdemic sites are mainly related to ethnic groups like: Malaysian Chinese, Chinese,Malays. Meanwhile, we can also see that keywords about identity and culture are used by scholars in both acdemic sites. Besides, we noticed that keywords from google scholar are more separated in topics, while keywords from baidu scholar are more foucused on ethic relations.

Protocol

example of protocol

This section is focused on “how ‘Malaysian Chinese’ is mentioned in academic area”. We started from Google Scholar and Baidu Scholar with the query “Malaysian Chinese”, “马来西亚华人”. For each query the first 20 papers were considered, so 40 results in total. Then we translated the Chinese keywords into English and made them into one visualization. The papers were downloaded, analyzed and tagged. The main dataset is composed by: id, link, title of the paper, author/s, information about the authors (job, studies, nationality and university), topic. After we organized the dataset in Excel we made the visualization in RawGraphs.

Data

Data Source: Google scholar,Baidu scholar
Timestamp: 19/11/2018
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