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D1
What is sentiment analysis? How does it relate to text mining? How can sentiment analysis be used in predicting financial markets?
Sentiment analysis is known as opinion mining, which entails determining the emotional tone behind a series of words that is used to gain a better understanding of attitudes, opinions and emotions expressed with an online mention. Sentiment analysis is useful when it comes to monitoring social media.
It allows analysts to monitor a wide view of public opinions. Sentiment analysis is tools that make the process quicker and easier based on the real-time capabilities. Sentiment analysis relates to text mining by analyzing unstructured content. Text mining extracts publicly available data sources such as: online reviews and social media discussions. Sentiment analyses are common in the financial sector to predict behavior and trends in stock markets.
D2
According to the textbook, sentiment analysis can also be called opinion mining, subjectivity analysis and appraisal extraction which deals with the automatic extraction of opinions, feelings in text, then these analysis results will provide businesses and individuals opportunities for future development. In a simple word, sentiment analysis is used to provide customers' feedback about services and products by using analytical methods to analyze textual data.
Texting mining has the same purpose and same process of data mining, but the data used in texting mining process is text-based data sources such as text excerpts, XML files and PDF files.
Since texting mining handles text-based data, it can be used as one of application to do sentiment analysis. Many text-based data can be collected, extracted and analyzed for positive or negative sentiment regarding particular opinion about services, politician or products.
From my understanding, sentiment analysis can be used to identify people's opinion about overall market trend, about some specific company's future development and about some specific incident, these opinions will affect stock marketing movements, especially the short term market.
For example, when North Korea stated that it will attack US, sentiment analysis is used to analysis people opinion about the statement, investors should get a conclusion that the market will go down in the short term, but after couple of days, when people calm down in social media and focus on other things, sentiment analysis will provide positive results about the market, so the investors should expect the market will go up again in the short term.
D3
Web analytics is the process of evaluation or analysis of a website, analytics measure activity and behavior of the website (ex: how many users visited the web page, how long they stay, which page and how many pages and did they reached the site by following some link or using keyword search). Web analytics is used for business and market research so that it would help improve the effectiveness of a website.
The benefits of web analytics:
• Web analytics provides insights of data which will be useful to create better user experience for website visitors
• Using web analytics, effectiveness of the online marketing campaigns can be accurately measured
There are three common types of web analytics metrics used:
Count - Count is the most basic unit of measure (ex: number of visits)
Ratio - Count divided by a count
KPI (Key Performance Indicator) - KPI can be either count or ratio, while basic counts ratios can be used by all websites types, a KPI is pervaded with business strategy.
Some of the most commonly used tools:
• Google Analytics - the ‘standard' website analytics tool, free and widely used
• Piwik - an open-source solution similar in functionality to Google and a popular alternative, allowing companies full ownership and control of their data
• Adobe Analytics - highly customizable analytics platform (Adobe bought analytics leader Omniture in 2009)
• Kissmetrics - can zero in on individual behavior, i.e. cohort analysis, conversion and retention at the segment or individual level
• Mixpanel - advanced mobile and web analytics that measure actions rather than pageviews
• Parse.ly - offers detailed real-time analytics, specifically for publishers
• CrazyEgg - measures which parts of the page are getting the most attention using ‘heat mapping'
• ClickTale - uses ‘heat mapping,' keystrokes and mouse movement