Blog post 6. Scraping the web for data
Written by Hyunjoung You
As Media Access Australia (n.d) states:
Twitter is a popular social networking tool that allows users to send a short, mostly text-based message up to 140 characters long known as a ‘tweet’. These tweets are then published online and can be publicly viewed. Twitter users can post their own tweets, follow the tweets of other users or contribute to a wider online discussion based on a particular topic or event.
Twitter is fast personal communication. People can share personal insights on something with other people. Moreover, they can follow the celebrities and send feedback on any events such as a live television show. It is also commonly referred to as a short web log (blog). Social Media News Australia reported that Twitter becomes Australia’s most popular social media microblogging tool with approximately 2.8 million unique visitors in Australia and over 300 million users worldwide in the early of 2016.
My research process
My specific topic is the association between sedentary lifestyle and obesity. Therefore, I searched using keyword ‘Obesity’, ‘Fat’, ‘Sedentary’, and ‘Lifestyle’ at first.
The data that came out on the list was exactly same as what I though about. However, as you can see the above screen shot, only one tweet showed since I used too specific keywords. I realized that I needed to use more general and suitable words to collect useful data.
This is the result by researching using keywords of ‘obesity’ and ‘fat’. I could receive lots of personal insights about obesity, but it was hard to find the information what I looked for because keyword was so broad to bring about specific data. Nevertheless, there were few results were related to my topic. After this, I searched using keywords ‘lifestyle’ and ‘office’ as well; however, it was not enough to gather useful data. Hence, I moved on Twitter search engine.
As you can see the above images, I typed three words ‘fat’, ‘sitting’, and ‘office’, which are more related to my topic. Many tweets came out, and they all indicated that sedentary work made them being fat. It shows that many people already recognize sedentary lifestyle is associated with obesity, but all tweets were their feelings about being fat like sad or anger. There were no any solutions or ideas for that issue.
While I scraped data via Twitter Archiver and Twitter search engine, I found how they were useful tool to discover information what I looked at using simple keywords. Twitter Archiver offered the list, which included the keywords I typed. It helped me to recognize what kinds of issues people share and discuss nowadays. Also, it provided wider knowledge that is related to obesity issue. Overall, I could have a look different personal insights and opinions about specific issues. It is really good to know them as a designer because we have responsibility to act for people needs and build the solutions to solve problems. Therefore, it is appropriate tool to scrape data to understand specific issue and personal insights.
Media Access Australia, n.d. ‘Twitter’, viewed 4 September 2016, <https://dev.twitter.com/overview/documentation>