From the very beginning, one of the core services TheWebMiner provided was aggregated data and insight into the mobile app landscape. We managed to offer our clients custom aggregated data for all major mobile app marketplaces (iOS AppStore, Google Play, Amazon AppStore etc.) as well as primary analysis on the extracted data.
I want to write now about a phenomena that is a part of our lives with or without our consent. I’m talking about Apple’s market strategy and how its intrusive policy of becoming one of the most exquisite brands have affected our perception on quality or innovation.
Further more, although the statistics that we found aren’t quite recent we can add that last week Apple inc. has sold 10 millions devices of its latest product, making it double than the original estimations. It would have been an even larger number but because of the major traffic that apple.com has had, the servers were down for a number of hours.
Now, in terms of data and what we are interested in, regarding the fact that all expectations were exceeded last week we can say that the only thing that is still bringing the money to Apple is the iPhone division. The sales of iPad are decreasing and so are the ones of Macs and iPods but even so the stocks listed are increasing their values. This can be explained only by following the history of the company from the day they were first listed back in the 90’s until now and observe that customer satisfaction and brand recognition as quality are one of the highest ever recorded.
In the end i’d like to say that even if Apple took its blows first with the competitive market of Android and Windows phones, later with the death of Steve Jobs and most recently with the flaws in the iCloud system that allowed hackers to break in and publish nude pictures of dozens of celebrities, marketing data reveals that the company is still in the top preferences of gadgets enthusiasts all over the world with a consolidated position over Samsung that will not decline too soon.
As you probably know, we deal everyday with data scraping, which is quite challenging, but, from time to time we tend to ask ourselves what else is there, and especially, can we scrap something else other than data? The answer is yes, we can, and today I am going to talk about how opinion mining can help you.
Opinion mining, better known as Sentiment analysis deals with automatically scan of a text and establishing its nature or purpose. One of the basic tasks is to determine whether the text itself is basically good or bad, like if it relates with the subject that is mentioned in the title. This is not quite easy because of the many forms a message can take.
Also the purposes that sentiment analysis can be to analyze entries and state the feelings it express (happiness, anger, sadness). This can be done by establishing a mark from -10 to +10 to each word generally associated with an emotion. The score of each word is calculated and then the score of the whole text. Also, for this technique negations must be identified for a correct analysis.
Another research direction is the subjectivity/objectivity identification. This refers to classifying a given text as being either subjective or objective, which is also a difficult job because of many difficulties that may occur (think at a objective newspaper article with a quoted declaration of somebody). The results of the estimation are also depending of people’s definition for subjectivity.
The last and the most refined type of analysis is called feature-based sentiment analysis. This deals with individual opinions of simple users extracted from text and regarding a certain product or subject. By it, one can determine if the user is happy or not.
Open source software tools deploy machine learning, statistics, and natural language processing techniques to automate sentiment analysis on large collections of texts, including web pages, online news, internet discussion groups, online reviews, web blogs, and social media. Knowledge-based systems, instead, make use of publicly available resources to extract the semantic and affective information associated with natural language concepts.
That was all about sentiment analysis that TheWebMiner is considering to implement soon. I hope you enjoyed and you learned something useful and interesting.
It’s very simple:
sqlite> .mode list
sqlite> .separator ,
sqlite> .output exported_file.csv
sqlite> select * from yourtable;
You can use other separator. For Microsoft Excel default separator is “;”.