Such data is not only useful for individuals but also for companies.On the one hand ,a lot of companies manufacturing such products have starter to poll these microblogs to get a sense of general sentiment for the product.Many time they analyse the data to study user reaction and reply to users.Here is an example for companies to do sentiment analysis:Twitter sentiment,a hedge fund named Derwent Capital Markets analyses the sentiment of uses of twitter to predict a stock.They focus on the feelings of a lot of users who are talking aboutstocks to help them.The picture blew illustrate the relationship between stock price and the emotion of twitter users:
On the other hand,choices individuals make are often conditioned upon how others see and evaluate.Therefore,we often seek out the opinions of others when we need to make a decision.That is way we should do Sentiment Analysis and Opinion Mining.When mining data ,we usually make large quantities of feedback more manageable by splitting them into cluster based on keywords.Sentiment analysis,which is the second step,adds a dimension to the data.It makes it possible to focus the mining on areas in need of negative feedback or positive feedback.In this case ,we should use Sentiment Classification (polarity detection)to estimate the polarity of the opinions of the writer.The first approach should consist of paying special attention to words that tend to express a positive or negative attitude.However,this may not be straightforward as one may think,given that sentiment is often expressed in more indirect way.Therefore,we should study more deeper in order to deal with this case.
As studying deeper and deeper ,I find what we learned in the class is really practical and useful.I will try to get a good command of it.
Hi, I am also seeking for materials which are related to what factors we should take into account when we interpret people's behaviour on social networks, would you recommend something to me?
回复删除Firstly, I want to say thank you for the computer network materials you sent to me! I was so grateful for your kindness to help me. I was inspired by your action. And I will send more information to you for sharing. Secondary, I also wrote something about opinion mining. As we view it in different aspects, it would be nicer to discus it together. Do you have some time to have a cup of coffee? I also find another classmates who are willing to discus about it,too. Maybe we can get together and learn from each other.
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回复删除Hi, Gao. I noticed that you mentioned When mining data ,we usually make large quantities of feedback more manageable by splitting them into cluster based on keywords.Sentiment analysis,which is the second step,adds a dimension to the data is very useful to me. Really look forward to discussing with you someday. Many thanks
回复删除Opinion mining is truly a significant measure of social media analysis. I use Weibo everyday to get some information and fun. I agree what we learned in the class is really practical and useful
回复删除The blog is inspiring, since I am investigating opinion mining recently!
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