I am based in Switzerland and I work in Market Research/Data Analysis. I need 2 separate projects completed.
Here I will focus on the first of these projects, relating to what is mentioned in the subject line: "Web Scraping with Sentiment Analysis"
It first concerns web scraping. I would like a program for Python that scrapes the web, all pages, and finds information about X (X = anything). I am not so interested in a specific result at the moment, meaning that I don't want you to find information about something. Instead I would like some code, elegantly written with comments, that is flexible for me to use, so I can substitute X with whatever is needed. An example of X will be "TSquared Insights" a Geneva based business. The program should be able to scrape all the web and gather data about all the places where TSquared Insights is present. The code should then be easy to use and understand, in terms of extracting detailed descriptive results from it. Like, in the example of TSquared Insights, it should be possible to see how many mentions there are of this company, temporal information about when most of this information first appeared and if there is a downward or upward trend (with less mentions on internet of the company, or more mentions) and also the type of pages where the information about the company appears (for example 26% on sport websites, 13% on health/beauty websites, ect..). So this is the web scraping part.
Then comes a Sentiment Analysis part. This would also be good if it were to be programmed in Python. The idea here is to compliment the web scraping part, by assessing what people say on Social Media regarding X. Social Media = Twitter and Facebook. The idea of this program is that it would bin social media text from users into two distinct bins (or groups). In the case of the above company TSquared Insights, the program should be able to assign all information about the company into bins that are either Positive or Negative. Again, I do not have a specific project or result in mind at the moment, so the code must be flexible enough so that when a specific project arises I can substitute Positive and Negative with, for example, Professional and Unprofessional (so gathering all the information from social media, where people talk about the company as either being professional or unprofessional). As for the web scraping, there would then have to be the easy possibility of generating informative descriptive data, like if the positive group is larger than the negative group, and the age-group, location, sex, browser type, ect of the people who say the Positive and the People who say the Negative.
One last thing; the Sentiment Analysis will likely be used more for specific products, rather than company names. Specific products means assessing the Sentiment on Social media relating to product X, and then repeating the analysis for product Y, and getting an idea of whether one is regarded as more Positive/Durable/Reliable than the other. This probably does not change anything to you (about the program having to do analysis more on products rather than on business names) but I thought I would tell you anyway.
If you think you are able to do this job, and do it to a high standard, I would love to hear from you.
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Have a nice day.
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I have been working in the field of Natural Language Processing, therefore , i find myself suitable for the given [login to view URL] to hear from you soon.
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Good evening! I have a lot of experience doing both web scraping and sentiment analysis in Python. You can check my portfolio on my profile for some examples. Could we discuss more details via chat please?