2013
Submitted To: Prof. Raleigh
06/07/2013
Text Mining
Submitted By: Roshan Bhattachan

What challenges does the increase in unstructured data present for businesses?
Text mining is the discovery of pattern and relationships from large set of unstructured data-the kind of data we generate in emails, phone conversation, blog posting, online customer surveys, and tweets (Laudon & Laudon, 2012). These unstructured data contains lots of useful information, and businesses can use this information to make a better decision making. The challenges for today businesses are how they can make best use of this unstructured information. It’s not a piece of cake to get information out easily because there are millions of information over the internet, and the success of businesses lies in how effectively and efficiently they can process and analyze this information , and use it to make better decision making. It’s a complex and rigorous tasks, and needs people time and money to take out best of information from this unstructured data.
How does text-mining improve decision making?
Text mining tools are now available to help businesses analyze unstructured data. These tools are able to extract key elements from large unstructured data sets, discover patterns and relationship, and summarize the information. For example: JetBlue in 2007 experienced a number of customer discontent which resulted in large number flight cancelation. It received around 15000 emails per day, and was not able to read all the emails. So, JetBlue with the help of Attensity, a leading vendor of text analytics software, was able to use software to analyze all the emails it received within two days. JetBlue was able to identify what were consumer complaints, and worked on the issue to give them better service and facilities (Laudon & Laudon, 2012). What we can clearly see is text mining facilitates gleaning from many unstructured text data and complies them. This data couldn’t be analyzed with decision making system like MIS and DSS because text mining is not structured data. Text mining improves decision making by offering unique insight into consumer behavior and attitudes (Rabu, 2013).
What kinds of companies are most likely to benefit from text mining software? Explain your answer?
The types of companies that are most likely to benefit from text mining software are government offices, large companies, restaurants, hotels, supermarkets etc. Some of the real life examples of text mining are: Gaylord Hotels and Choice hotels are using text mining software to glean insights from thousands of customer’s satisfaction surveys provided by their guests. Gaylord hotel is using Clarabridge’s text analytics solution delivered via the internet as a hosted software service to gather and analyze customer’s feedback from surveys, email, chat messaging, staffed called centers, and online forums associated with guests and meeting planners. Similarly airline industry like JetBlue in 2007 experienced a number of customer discontent which resulted in large number flight cancelation. It received around 15000 emails per day, and was not able to read all the emails. So, JetBlue with the help of Attensity, a leading vendor of text analytics software, was able to use software to analyze all the emails it received within two days. JetBlue was able to identify what were consumer complaints, and worked on the issue to give them better service and facilities (Laudon & Laudon, 2012).
In what ways could text mining potentially lead the erosion of personal information privacy? Explain.
Technology has been a blessing for many of us. But, the drawback of technology is that it hinders the privacy. Company tends to use and manage personal information for their business. Mobile companies manages huge amount of privacy data as structured data. But, sometimes hacker can go inside these databases and misuse the data (riyanti, 2012). Similarly, IRS can get the personal health information of individual which hampers ones privacy. Another latest issue is that government agencies now can track all the phone calls and messages of the people which are not ethical. In conclusion, text mining has made information open and easily accessible. Due to which there can be personal issues in one’s life, confidential information about people can easily be tracked like bank account and may result in fraud. Crimes can be conducted by using other people identity, and as a result of which innocent people can be convicted for the crime they have not committed.

Reference 1. Laudon, K., & Laudon, J. (2012). Management information system. (12 Ed.). New Jersey: Perentice hall. 2. Rabu. (2013, 04 03). What can businesses learn from text mining? 3. riyanti, R. (2012, 04 05). database and information management.