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Data Science

How to Interpret Texts

If you have data regardless of whether they are obtained from social media or other sources, the next step is to analyze the meaning of those data. However, it is difficult to interpret the natural language in terms of sentiment analysis. Fortunately, there are several ways to understand text data and even provide quantification. TextBlob […]

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Data Science

How to Collect Tweets for Analysis

To analyze how a certain service or product is accepted in a market, many people have tried certain traditional methods such as market survey and FGI. However, it requires expenses and has some limitations of space and time needed to design the research from laying out questionnaire to obtaining survey respondents. There is a simpler […]

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Data Science

[Clustering Analysis in R] #4. Data Analysis

Finally, we can step into the process for clustering analysis, which is to separate customers for their characteristics and to find representative tendency of each group (segment). To that end, I will use two approaches: k-means and hierarchical clustering analysis. The former is to find if independent groups have high similarity from their representative observation […]

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Data Science

[Clustering Analysis in R] #3. Data Diagnostics

Now, we need to diagnose whether these data are adequate for analysis in a way that those results are not originated from biased sample distribution and correlated variables. To that end, muliticollinearity test clarifies correlation between independent variables and I used corrgram() for that matter, which is one of the packages in R. > install.packages(“corrgram”) […]

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Data Science

[Clustering Analysis in R] #2. Data Processing

By and large, there are two types of data: quantitative and qualitative data. If you want to do any kind of analysis such as regression and classification, you need to transform qualitative data to quantitative. Most data that have a category can be transformed to dummy variable. For instance, male can be zero and female […]

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Data Science

[Clustering Analysis in R] #1. Introduction & Data Gathering

  Before Starting the Process The reason why I have started writing these postings is because, as a beginner and learner of data science, I wanted to share my knowledge about clustering analysis and develop them based on active discussions. Main objective of these postings is to understand the whole process from data gathering to […]

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Business

Most Important Thing for Card Issuers during Big Data War

There was an interesting article about big data based businesses of major credit card companies in Korea. According to Korea Economic Daily, two major card companies, Shinhan and Samsung, see big data as a new business opportunity while Hyundai Card is skeptical about it. Recently Shinhan and Samsung are each driving their data based services. […]

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Data Science

How to Retrieve Data from Google Sheet

R data is huge, so it is general to analyze on a desktop (local computer) or a server which provides better computing power. However, the former is inconvenient when you analyze data without your computer while the latter requires a complicated set-up process. There is an option to use cloud DB without paying money: Google […]

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Data Science

How to Insert Interactive Tables and Charts into WordPress

There are several ways to put graphs and tables into a blog on WordPress. One of them is Visualizer plug-in, which is easy to handle and straightforward to input data. [ Barchart using Visualizer (example: Monthly Bill for Utility) ] [visualizer id=”1656″] However, the plug-in is limited to use CSV file and does not reflect […]

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Business

Rapid Growth of Mobile Games and SundayToz

Recently in Korea, there was a news report that major shareholders in SundayToz sold their shares to SMILEGATE. SundayToz is a mobile game developing company established in 2009. The company was positioned as the number one social game developing company in Korea since its Anipang series became a hit, recording 28 million downloads. Their newly […]