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This study was divided into three parts. The first part was to design and create a Chinese word segmenting custom dictionary specifically for the RFID Technology and Certification course to improve the accuracy of the word segmentation. The second part was to apply the text sentiment analysis to figure out the positive and negative emotions of students in the discussion of the course so that the teachers could quickly browse the students’ discussion, and find out any situation requiring further notice. The third part discovered that the relevance of the discussion to the course content was positively correlated with the emotions shown in the discussion.

The price of bitcoin has changed significantly in recent years. At the same time, there are abundant media attention and news coverage of Bitcoin. This research applied Python to crawl Bitcoin daily exchange data and Google search volume index (SVI) from Coinmarketcap.com and Trends.Google.com and to conduct data cleaning to make the collected search volume data unified and comparable in a time series. This paper focuses on the association between SVI and changes in Bitcoin price. Specifically, this study looks into correlations between SVI, Bitcoin returns, and price volatilities by conducting a vector autoregression model. The results show that SVI has an evidently positive influence on both the return and volatility of Bitcoin, which means SVI could be used as an effective predictor in forecasting Bitcoin earnings. This paper enriches research on the impact of the Bitcoin search volume index on prices, which indicates that SVI is a meaningful evaluation index to invest in Bitcoin.

The famous theory “Six Degrees of Separation” states that any two people around the world could connect with each other through an average number of six steps. In this paper, an attempt was made to analyze the Six Degrees of Separation in Baidu Encyclopedia which has included more than 1300, 0000 articles as of April 2016. A web crawler is built to get the links of articles in Baidu Encyclopedia and MySQL database is established to store the information in an architecturally sound way to make data analysis easy. The minimum number of links between any two unlikely articles was identified efficiently by using Breadth-First Search. According to the simulation result, even “Five Degrees of Separation” still holds in Baidu Encyclopedia; an article could get to 78% of all other articles within five links.

With the rapid development of Open Source Software (OSS), a lot of reusable software resources have been produced in open source communities. This leads to spotty quality and high dispersion of OSS resources so that lots of research works have been conducted for effective location of reliable software resources. To provide convenient data source for such studies, this paper introduces Octopus, a data acquisition system for resource of open source software. Octopus is a robust, scalable and efficient system which consists of three main modules that have been well decoupled and can be updated at runtime with flexible configurations. The experiment results show that, Octopus can successfully collect two kinds of OSS data sources: software production communities and software consumption communities. The former produce structured software artifacts such as project profiles while the latter contain rich user feedback such as posts and blogs.