Today, data scraping plays an increasingly strategic and important role in identifying trends, analysing the use of products and setting up marketing strategies.
The term “web scraping”, from the verb “to Scrape”, is a Crawling technique. A crawler is a software that aims to collect all the information needed to index the pages of a site, find associations between search terms and analyse hyperlinks. The purpose is to extract data and then collect them in databases and get various useful information.
This technique is widely used by all search engines, first of all Google, in order to offer users always relevant and updated results.
The methodology of web scraping
Different methodologies can be implemented to obtain data from the network and web portals, all sharing the use of APIs that allow you to quickly access online pages to extract information.
Exploiting bots and other automated software systems these methods simulate the online browsing of human users and require access to web resources just like in the case of a normal browser. The server will respond by sending all the requested information that will be collected in large databases and catalogued as Big Data.
Today, the following methods are mainly used:
- Manual: when there’s not much data required, you can copy and paste it manually. This methodology is rarely the best because it requires a lot of time and resources.
- Parser HTML o XHTML: The pages of many websites are made in a markup language, usually HTML. Being structured with HTML tags, you can parse the page and get the content of a TAG that contains the data you are interested in.
- Web Mapping: with the passing of the years have been realized various software and tools able to recognize automatically the structure of the web page and go to “fish” the required information without any human intervention is necessary.
- Computer Vision: using machine learning, it is possible to use “web harvesting” techniques that analyse web pages following the same procedure as a human user. This greatly reduces the work required of web scraping software and results in more relevant information.
Is the web scraping legal?
“If your content can be viewed on the web, it can be scraped” Rami Essaid, CEO and co-founder of Distil Networks.
Web scraping is legal as long as the analyse d data are accessible directly on the sites and are used for statistical or content monitoring purposes.
Sentiment Analysis: why is it so important for companies?
In the era of the Data Economy, web scraping techniques play a fundamental role in identifying trends, conducting statistical surveys and understanding user sentiment. Sentiment Analysis can be defined as an activity focused on analysing and listening to the web with the aim of understanding people’s opinions about a brand and/or service-product. Thanks to this practice today companies have the opportunity to have much more information related to the simple perception of users.
What are the main advantages?
- Identify industry trends and tendencies to stay up to date on changes in the market
- Analyse statistics to evaluate the right brand strategy
- Acquire competitive advantages and know competitors’ strategies in real time, for example prices and products
- Protect the company reputation and intervene promptly in case of crisis or damage to image
- Get immediate feedback after launching a new product or service.
Knowing the different types of Sentiment Analysis is essential to understanding which one to use for achieving a business goal:
- Detailed analysis: provides a detailed understanding of the feedback received from users. Precise polarity results can be obtained on positive or negative scales (with increasing numbering, from 1 to 10).
- Emotional analysis: aims to detect emotions using complex machine learning algorithms that analyse the lexicon.
- Product Aspect Based Analysis: this type is conducted for a single aspect of a service or product in order to have precise feedback on a specific feature.
- Intention Analysis: it allows to have a deeper vision of the intention of the customer. Understanding the latter can be useful to identify a “basic” consumer model in order to set up a proper and efficient marketing plan
Semantic Recognition Engine of Drive2Data
At Drive2Data, experts in Data Quality and Data Intelligence, we have carried out several studies on the processes of Sentiment Analysis. Using the application of Natural Language Processing (NLP) and using Deep Learning models.
A tool that returns information about the context of sentences, recognizing their emotions, with the aim of helping companies to manage the analysis of the feeling automatically and quickly.
We strongly believe that technology, when used properly, can help make the world safer and more sustainable.