#reviewgators

Data extraction, according to our users, can be a difficult aspect of the systematic review process.

Data extraction is the process of locating and extracting data from study reports so that similar data from multiple sources can be analyzed. It's an essential component of any methodical or scientific review process, as it enables you to assemble a large sufficient dataset to (hopefully!) provide meaningful evidence.

Create a Plan

It's essential to schedule out the process before you start and clearly explain and record your inclusion and exclusion criteria that are likely to grab the information that will help answer your research question, as well as how to set up your data extraction form to capture this information effectively. This can be anything from a simple outline to a published, peer-reviewed protocol; however, you present it, it's important to plan out your process before you start and clearly define and document your inclusion and exclusion criteria that are likely to capture the data that will help.

Execute a Pilot

Create a system for testing your strategy and communicating with your co-reviewers. Each phase of the review process should be piloted, beginning with screening to ensure that all assessors are aware of and agree on the criteria. When beginning data extraction, a second round is useful to check that the team is gathering the data required for an efficient analysis (and also that all reviewers are extracting data consistently). Piloting quality evaluation guarantees that all examiners are familiar with and agree on the rating methodology.

Collect Necessary Documents

It's critical to maintain writing precisely why you're doing it and how you're doing it as you start to put your theory into action. It's vital to be open about your approach so that even if another reviewer followed it, they'd receive the same result. It may even be important to modify principles and requirements to the requirements of your enterprise or discipline, so be as transparent as possible about how you arrived at your judgments, whatever informed you, and any change requests you made.

Provide Enough Time

The process frequently takes significantly longer than anyone expects; it's critical to factor in anticipated delays in the project schedule. Set precise targets and deadlines to allow your team to check-in, examine what you've all done so far, and address any issues that have occurred and how to best fix them during the pilot phase.

Search for a Mentor

When conducting a research study or systematic review for the very first time, there is a lot to learn and grasp; guidance or mentoring from somebody who has accomplished it before will make all the difference in completing the process effectively. They can function as just an independent reviewer to ensure that your team's screening or extraction is up to standard, or they can collaborate directly with you to make procedure and process choices. Your procedure will be less stressful and more productive with the help of a mentor.

As we know data is the most necessary component for web scraping review data. A review management platform is powered by online reviews, such as a car is powered by energy or gas. While there are various sources of user reviews such as ReviewGators Review Scraper API.

As a result, we set out to address our own challenges, and we've learned a lot in the process. We began by using these product reviews in our own tool but quickly discovered that we could market this technology so that others could advantage from such an easy API rather than scraping reviews manually.

This was a turning point in our capacity to invest more heavily in this product, not only for ourselves but also for paying users. Following are some of the lessons we learned along the journey.

API vs Scraping

In an ideal society, review data would be accessible using API, however, that's not the case. We employ APIs whenever possible, however, the majority of the 85+ review sites from which we get information don't have APIs, so we have to rely on web scraping. We also have connections with particular review websites in some circumstances.

Select Scraping Library

First and foremost, what programming language would you prefer to use? Which scraping library you use will be determined by this. Python offers Scrapy, Ruby has Nokogiri, and there are plenty of additional possibilities.

There are various factors to consider here, for example: How reliable is the library you've selected? How easy is it to find talented programmers who have worked with that library before? Is it scalable in any way?

Our system was written in Ruby because it was my strongest language at the time. This influenced a number of decisions, including the use of Sidekiq for background processing and ActiveAdmin for the admin panel, among others.

At ReviewGators, we create scrapers that follow the specific format:

Determine the number of pages of reviews that can be paginated.

Determine which markup contains the reviews.

Iterate through each review and save the information.

In other circumstances, utilizing a network analyzer is beneficial since some websites load their data via APIs, which are easier to use (and maintain) than parsing code. Another consideration is whether the website is loaded asynchronously, in which case you should employ a headless browser rather than a standard HTTP request.

Concurrency

It's important to think about how you'll deal with concurrency when you've created the scraper, depending on the scale you'll be scraping reviews on. We chose Sidekiq to process our operations in the background because it allows us to easily manage many queues and scale vertically and horizontally as needed. We also utilize sidekiq-throttled to make sure we're not overloading the review site and our vendors with queries.

We started encountering database concurrency issues as our business developed, so we made a number of database adjustments to improve our workload.

Blocking Mechanisms

You'll very certainly run across blocking mechanisms from the review site(s) in question as you start scaling up. This problem can be solved in various ways:

Scraping services that allow you to access a URL and have them handle the blocking measures on their end.

Providers of proxy IP addresses for data centers, homes, and mobile phones.

Captcha-solving services that automate the process at a large scale.

Headless browser services make it easier to manage headless browsers on a large scale.

To get around blocking measures on some sites, you'll need to send requests with specific headers and/or cookies, as well as a variety of additional techniques.

Duplications

You'll want to optimize your scraping once you've started scraping reviews at scale to stop spending compute and other assets. You'll probably want to keep retrieving the latest reviews as they come in after you've fetched all the reviews from a certain review profile.

To accomplish this, you'll need to create algorithms that identify which reviews are old and which are new. This is far more difficult than it appears at first, as there are several formatting, pagination, ordering, and other issues. If the review profile has 100 pages, your goal is to stop scraping once you've collected all of the most recent reviews, so you don't have to check all of them every time you check for updates.

Several settings are exposed to our users that encapsulate this complexity:

Diff: This argument allows you to specify a previous work ID for your specified profile, ensuring that only the most recent reviews are returned.

From_date: Reviews from a particular date will only be scrapped.

blocks: The number of blocks to return from the results in tens.

Data Cleaning

Data cleaning is an important element of data extraction since you must always guarantee that the information you consume is in a consistent manner. To begin, we recommend encoding your database to utf8mb4-bin, which supports text in a variety of languages, as well as emoji and other text that you will undoubtedly encounter.

Date formatting is extremely difficult, especially when scraping from various sources. This is due to the fact that there is no universal date format; for example, Americans may use yyyy-mm-dd, while other countries use yyyy-dd-mm. To make matters worse, we've observed occasions where the same review site employs several formats.

Aside from that, some websites contain reviews with headers, questions, and other metadata that must be handled.

Monitoring

We consider monitoring as a serious matter. In the worst-case situation, we receive emails from a customer informing us of a problem, which is when our monitoring system kicks in.

Keep track of the progress of every work that comes through our system.

Wait and process times per job are being tracked, with averages across sites.

Keeping track of the performance of our numerous service providers.

Tests of each review site on a regular basis, comparing expected and real-time outcomes.

We have a substantially modified ActiveAdmin dashboard that allows us to monitor and intervene as needed. We also utilize Rollbar for real-time analytics and Asana automation to assist with issue management.

Conclusion

Operating a high-quality web scraping business on a large scale is a difficult task. Fortunately, we've got our technology available through API, so instead of spending significant technical resources rebuilding the wheel, all you have to do is call two API endpoints.

For more details contact ReviewGators now!!

We have a lot of opportunities in today's digital world to gain a lot of knowledge about a business brand or product by simply reading its evaluations. About 70% of current consumers say that they carefully examine, research, and evaluate reviews and that they place more trust in businesses that have received positive feedback.

Customers can now freely share their experiences and opinions about a variety of companies, commodities, and services through a variety of online platforms. People will be able to scrape client reviews and use this vital knowledge to their advantage. The information collected can help businesses and e-commerce entrepreneurs provide a better customer experience to their customers.

Amazon, Yelp, and TripAdvisor are just a few of the massive platforms that compile millions of buyer reviews about their expertise with a certain brand. You can scrape any reviews (or feedback), as well as questions and answers regarding particular products, and extract useful information from them.

What is the Importance of Customer Review Scraping in Business and E-Commerce?

Initially, certain purchasers may care about reviews while considering a purchase. This type of consumer content has the ability to transform enterprises. Scraping a webpage and evaluating customer data can be extremely beneficial for market analysis, marketing plans, competitor analysis, and other purposes. Web scraping services can help entrepreneurs make informed, data-driven decisions that will help them build their business and acquire consumer loyalty in a variety of ways.

Initially, you may learn about your consumers' likes and dislikes and be updated about them at all times. You may figure out your competitive advantage, discover your weaknesses, and enhance them with the help of direct responses from your clientele.

Then, you have complete freedom to monitor the evaluations of your competitors' clients in order to stay updated on them and their general market position. It will assist you in performing a market and trend analysis, as well as customizing your business and service to stay ahead of the competition.

There are several benefits to maintaining track of customer feedback. At the same time, scraping customer reviews is simple: a web scraper visits a website or a web platform and grabs all of the information that interests you. The unstructured data is then collected, evaluated, and delivered to you in a usable format.

Why Do You Need Review Scraping?

New evaluations surface on websites across the internet every second. There are dedicated review platforms, company websites with feedback sections, and social media outlets, which together allow businesses to create profiles with comment threads, evaluations, blogs, newsgroups, and other features. It's tough to comprehend the whole scale and power of today's internet, and manually scraping all of these reviews is simply impossible.

Furthermore, many web portals are already overburdened with false or untrustworthy information. Aside from that, personally analyzing this data would be incredibly time-consuming and costly.

Modern web robotics and machine learning digital signal the use of powerful data scraping technologies that can do tasks fast and efficiently according to your specifications. This method of web review scraping will allow you to gain insight into consumer opinions and acquire meaningful insights and improve business operations, customer support, and enhance your item or brand. It's important to remember that bad evaluations are just as important as positive reviews, if not more so because they're your form of education and development zone indicators.

How to Use Customer Reviews to Boost Your Business?

Analysis of Your Company's Reviews

You may gain an overall grasp of customers' opinions toward your business, their loyalty, and their contentment by scraping reviews and ratings from numerous web pages. While a rating-based evaluation is useful for this, you need to go deeper and check feedback as well. Poor wrapping or shipping, that might or might not be within your direct control, maybe the source of dissatisfaction or disappointment. However, if such a leads to low client satisfaction, you should think about how to enhance it.

Competitor’s Business Reviews Monitoring

You may better understand your competitors' qualities and weaknesses by using web scraping technologies to research them. This will help you improve your company's market position. Try to exceed competitors in the areas that their customers care about, and learn about their customers' primary grievances and pain spots. You can also keep track of disappointed clients and provide them with solutions.

Comparison with Competitor’s Business

When you collect evaluations regarding your company and your competitors, you can analyze them and obtain useful insights and understanding that need to be improved, strategies for gaining a competitive advantage, marketing tactics to explore, and much more.

Revealing the Startup's Prospects

Review scraping can inform you of the challenges consumers encounter in a given particular market segment if you do not currently have a business but are considering starting one. You may then provide a unique, original solution to their problems and establish yourself as a market leader.

More Client Awareness

You can better satisfy your customers' needs, give more effective service, and supply high-quality items if you understand their choices and preferences.

Fraud Detection

Web crawlers can assist you in detecting market scams, or at very least detecting indicators of such an issue. You'll be able to please and gain their loyalty if you attempt to retain dissatisfied clients. If you can locate unsatisfied partners, you may form some kind of mutual gain partnership that will help your company flourish.

All you have to do is search the web using a web scraping tool that best suits your needs and looks for the most cutting-edge solution for your organization.

The Most Famous Sources and Web Platforms

Every new website, site, or network contains a wealth of business-related information. However, each of the most famous review scraping tools has its own set of advantages. While Amazon and eBay are the finest places to go for product reviews, TripAdvisor and Booking are excellent places to look for feedback on travel and tourism attractions. Because of its open reviews of businesses and services, Yelp has transformed the commercial environment. More information on each of the sites:

Amazon: Customers leave millions of reviews and ratings on Amazon about the things they purchase and sell. About 60% of Amazon customers in the United States say they trust customer reviews.

TripAdvisor: is the most popular travel website. It also offers a substantial quantity of client comments on hotels, restaurants, and other destinations visited.

Glassdoor: is a website that gathers comments and feedback about specific employers' working environments. Glassdoor evaluations can be scraped for pay data, upper executives’ attitudes toward employees, and a variety of other useful information.

Yelp: provides reviews of goods and services, primarily for local markets, and 90 percent of users admit having read service ratings first and making a decision depending on comments. As a result, web scraping from Yelp can be beneficial for small and medium-sized business research and development.

Google Places: Similar to Yelp, Google Places can provide you with reviews of local businesses.

ReviewGator Services

Data delivery and custom scraping tool development are two approaches to web data scraping and review scraping in particular. In the first example, we extract and analyze information, clean it up, and then give it to you to evaluate. We may indeed develop a unique web application for your company with complex functionality. It will be able to scrape your desired information on its own.

If you are looking to scrape opinions about goods and services, then contact ReviewGators today!!

A guide to using Python to Scrape Android App Reviews and turn the data into a sentiment analysis database.

Let's look at how to scrape reviews and ratings for Android apps to produce a dataset for sentiment analysis. You'll save the material to CSV files after converting the application and reviewing the data into Data Frames.

Executing the code with Scripting with Pytorch (Google Colab)

Installing necessary packages and setting up the imports

You'll learn how to:

Establish an objective and criteria for including your dataset.

Look for real-world consumer comments on the internet.

Use Pandas to convert and store the dataset into CSV files, which you can find on Google Play.

The Dataset's Purpose

Setup:

import json import pandas as pd from tqdm import tqdm import seaborn as sns import matplotlib.pyplot as plt from pygments import highlight from pygments.lexers import JsonLexer from pygments.formatters import TerminalFormatter from google_play_scraper import Sort, reviews, app %matplotlib inline %config InlineBackend.figure_format='retina' sns.set(style='whitegrid', palette='muted', font_scale=1.2)

The Target of the Dataset

You'd like to receive customer feedback on your items, whether positive or negative; both are valuable. You'd want to know what other people think of your app. Both the negative and positive features are advantageous. The negative one, on the other hand, may reveal critical features that are missing or service disruptions (when it is much more frequent).

Fortunately, Google Play offers a diverse selection of apps, ratings, and reviews. We can scrape app metadata and reviews using the google-play-scraper program.

When it comes to evaluating apps, you have a lot of alternatives. On the other hand, different app categories have diverse target audiences, domain-specific characteristics, and so on. Let's start with the fundamentals.

We need applications that have been around for a long so that natural feedback may be gathered. We want to keep the amount of advertising we utilize to a minimum. Because apps are updated on a regular basis, the date of the review is crucial.

In a perfect world, you'd collect every possible review and use it to your advantage. In the real world, however, data is frequently restricted (too large, inaccessible, etc.). As a result, we'll give it our all.

Let's take a look at a few apps that meet the Productivity category's requirements. We'll use AppAnnie to select a few of the most popular apps in the US:

app_packages = [ 'com.anydo', 'com.todoist', 'com.ticktick.task', 'com.habitrpg.android.habitica', 'cc.forestapp', 'com.oristats.habitbull', 'com.levor.liferpgtasks', 'com.habitnow', 'com.microsoft.todos', 'prox.lab.calclock', 'com.gmail.jmartindev.timetune', 'com.artfulagenda.app', 'com.tasks.android', 'com.appgenix.bizcal', 'com.appxy.planner' ]

Extracting App Information

Scraping the information for every application

app_infos = [] for ap in tqdm(app_packages): info = app(ap, lang='en', country='us') del info['comments'] app_infos.append(info) For each of the 15 apps, we are able to gather information. Let's create a method to make printing JSON objects easier: def print_json(json_object): json_str = json.dumps( json_object, indent=2, sort_keys=True, default=str ) print(highlight(json_str, JsonLexer(), TerminalFormatter())) Here's an example of app data from the list: print_json(app_infos[0]) { "adSupported": null, "androidVersion": "Varies", "androidVersionText": "Varies with device", "appId": "com.anydo", "containsAds": null, "contentRating": "Everyone", "contentRatingDescription": null, "currency": "USD",  "description": "\ud83c\udfc6 Editor's Choice by Google\r\n\r\nAny.do is a To Do List, Calendar, Planner, Tasks & Reminders App That Helps Over 25M People Stay Organized and Get More Done.\r\n\r\n\ud83e\udd47 \"It\u2019s A MUST HAVE PLANNER & TO DO LIST APP\" (NYTimes, USA TODAY, WSJ & Lifehacker).\r\n\r\nAny.do is a free to-do list, planner & calendar app for managing and organizing your daily tasks, to-do lists, notes, reminders, checklists, calendar events, grocery lists and more.\r\n\r\n\ud83d\udcc5 Organize Your Tasks & To-Do List in Seconds\r\n\r\n\u2022 ADVANCED CALENDAR & DAILY PLANNER - Keep your to-do list and calendar events always at hand with our calendar widget. Any.do to-do list & planner support daily calendar view, 3-day Calendar view, Weekly calendar view & agenda view, with built-in reminders. Review and organize your calendar events and to do list side by side.\r\n\r\n\u2022 SYNCS SEAMLESSLY - Keeps all your to do list, tasks, reminders, notes, calendar & agenda always in sync so you\u2019ll never forget a thing. Sync your phone\u2019s calendar, google calendar, Facebook events, outlook calendar or any other calendar so you don\u2019t forget an important event.\r\n\r\n\u2022 SET REMINDERS - One time reminders, recurring reminders, Location reminders & voice reminders. NEW! Easily create tasks and get reminders in WhatsApp.\r\n\r\n\u2022 WORK TOGETHER - Share your to do list and assign tasks with your friends, family & colleagues from your task list to collaborate and get more done. \r\n\r\n---\r\n\r\nALL-IN-ONE PLANNER & CALENDAR APP FOR GETTING THINGS DONE\r\nCreate and set reminders with voice to your to do list. \r\nFor better task management flow we added a calendar integration to keep your agenda always up to date. \r\nFor better productivity, we added recurring reminders, location reminders, one-time reminder, sub-tasks, notes & file attachments. \r\nTo keep your to do list up to date, we\u2019ve added a daily planner and focus mode.\r\n\r\nINTEGRATIONS\r\nAny.do To do list, Calendar, planner & Reminders Integrates with Google Calendar, Outlook, WhatsApp, Slack, Gmail, Google Tasks, Evernote, Trello, Wunderlist, Todoist, Zapier, Asana, Microsoft to-do, Salesforce, OneNote, Google Assistant, Amazon Alexa, Office 365, Exchange, Jira & More.\r\n\r\nTO DO LIST, CALENDAR, PLANNER & REMINDERS MADE SIMPLE\r\nDesigned to keep you on top of your to do list, tasks and calendar events with no hassle. With intuitive drag and drop of tasks, swiping to mark to-do's as complete, and shaking your device to remove completed from your to do list - you can stay organized and enjoy every minute of it.\r\n\r\nPOWERFUL TO DO LIST TASK MANAGEMENT\r\nAdd a to do list item straight from your email / Gmail / Outlook inbox by forwarding [email protected]. Attach files from your computer, Dropbox, or Google Drive to your to- tasks.\r\n\r\nDAILY PLANNER & LIFE ORGANIZER\r\nAny.do is a to do list, a calendar, an inbox, a notepad, a checklist, task list, a board for post its or sticky notes, a task & project management tool, a reminder app, a daily planner, a family organizer, an agenda, a bill planner and overall the simplest productivity tool you will ever have. \r\n\r\nSHARE LISTS, ASSIGN & ORGANIZE TASKS\r\nTo plan & organize projects has never been easier. Now you can share lists between family members, assign tasks to each other, chat and much more. Any.do will help you and the people around you stay in-sync and get reminders so that you can focus on what matters, knowing you had a productive day and crossed off your to do list.\r\n\r\nGROCERY LIST & SHOPPING LIST\r\nAny.do task list, calendar, agenda, reminders & planner is also great for shopping lists at the grocery store. Simply create a list on Any.do, share it with your loved ones and see them adding their shopping items in real-time.",  "descriptionHTML": "\ud83c\udfc6 Editor's Choice by Google Any.do is a To Do List, Calendar, Planner, Tasks & Reminders App That Helps Over 25M People Stay Organized and Get More Done. \ud83e\udd47 "It\u2019s A MUST HAVE PLANNER & TO DO LIST APP" (NYTimes, USA TODAY, WSJ & Lifehacker). Any.do is a free to-do list, planner & calendar app for managing and organizing your daily tasks, to-do lists, notes, reminders, checklists, calendar events, grocery lists and more. \ud83d\udcc5 Organize Your Tasks & To-Do List in Seconds \u2022 ADVANCED CALENDAR & DAILY PLANNER - Keep your to-do list and calendar events always at hand with our calendar widget. Any.do to-do list & planner support daily calendar view, 3-day Calendar view, Weekly calendar view & agenda view, with built-in reminders. Review and organize your calendar events and to do list side by side. \u2022 SYNCS SEAMLESSLY - Keeps all your to do list, tasks, reminders, notes, calendar & agenda always in sync so you\u2019ll never forget a thing. Sync your phone\u2019s calendar, google calendar, Facebook events, outlook calendar or any other calendar so you don\u2019t forget an important event. \u2022 SET REMINDERS - One time reminders, recurring reminders, Location reminders & voice reminders. NEW! Easily create tasks and get reminders in WhatsApp. \u2022 WORK TOGETHER - Share your to do list and assign tasks with your friends, family & colleagues from your task list to collaborate and get more done. --- ALL-IN-ONE PLANNER & CALENDAR APP FOR GETTING THINGS DONE Create and set reminders with voice to your to do list. For better task management flow we added a calendar integration to keep your agenda always up to date. For better productivity, we added recurring reminders, location reminders, one-time reminder, sub-tasks, notes & file attachments. To keep your to do list up to date, we\u2019ve added a daily planner and focus mode. INTEGRATIONS Any.do To do list, Calendar, planner & Reminders Integrates with Google Calendar, Outlook, WhatsApp, Slack, Gmail, Google Tasks, Evernote, Trello, Wunderlist, Todoist, Zapier, Asana, Microsoft to-do, Salesforce, OneNote, Google Assistant, Amazon Alexa, Office 365, Exchange, Jira & More. TO DO LIST, CALENDAR, PLANNER & REMINDERS MADE SIMPLE Designed to keep you on top of your to do list, tasks and calendar events with no hassle. With intuitive drag and drop of tasks, swiping to mark to-do's as complete, and shaking your device to remove completed from your to do list - you can stay organized and enjoy every minute of it. POWERFUL TO DO LIST TASK MANAGEMENT Add a to do list item straight from your email / Gmail / Outlook inbox by forwarding [email protected]. Attach files from your computer, Dropbox, or Google Drive to your to- tasks. DAILY PLANNER & LIFE ORGANIZER Any.do is a to do list, a calendar, an inbox, a notepad, a checklist, task list, a board for post its or sticky notes, a task & project management tool, a reminder app, a daily planner, a family organizer, an agenda, a bill planner and overall the simplest productivity tool you will ever have. SHARE LISTS, ASSIGN & ORGANIZE TASKS To plan & organize projects has never been easier. Now you can share lists between family members, assign tasks to each other, chat and much more. Any.do will help you and the people around you stay in-sync and get reminders so that you can focus on what matters, knowing you had a productive day and crossed off your to do list. GROCERY LIST & SHOPPING LIST Any.do task list, calendar, agenda, reminders & planner is also great for shopping lists at the grocery store. Simply create a list on Any.do, share it with your loved ones and see them adding their shopping items in real-time.",  "developer": "Any.do Calendar & To-Do List",  "developerAddress": "Any.do Inc.\n\n6  Agripas Street, Tel Aviv\n6249106 ISRAEL",  "developerEmail": "[email protected]",  "developerId": "5304780265295461149",  "developerInternalID": "5304780265295461149",  "developerWebsite": "https://www.any.do",  "free": true,  "genre": "Productivity",  "genreId": "PRODUCTIVITY",  "headerImage": "https://lh3.googleusercontent.com/dZknnlk1LM8fYS3wjOvVHOmWKOGH1HAe691Yuh7LAeBj6a730A1CQqZnXxjNahAYUFFw",  "histogram": [27291, 9246, 13735, 29904, 262997],  "icon": "https://lh3.googleusercontent.com/zgOLUXCHkF91H8xuMTMLT17smwgLPwSBjUlKVWF-cZRFjlv-Uvtman7DiHEii54fbEE",  "installs": "10,000,000+",  "minInstalls": 10000000,  "offersIAP": true,  "price": 0,  "privacyPolicy": "https://www.any.do/privacy",  "ratings": 343174,  "recentChanges": "Faster and smoother for better user experience!",  "recentChangesHTML": "Faster and smoother for better user experience!",  "released": "Nov 10, 2011",  "reviews": 122170,  "score": 4.43388,  "screenshots": [    "https://lh3.googleusercontent.com/C-L3_FPMlKVrZItAORaszhnQzlzMyXcqF_-oGaabHm_OnwUW1jz02BXBVSKi0HRUtQ",    "https://lh3.googleusercontent.com/uAP6G5ANQcgVs4Uj6yrcsAo4OUhejTJRVCXOxnAVA5Efit_OtAnrOYyL1SUHj1rv",    "https://lh3.googleusercontent.com/AI5mLFu0Atsl0km2FO9_IwJXNy_1q1_X6Ua3EVMZNedp0dsDToDRaWQ1UDvI6mb1-I0",    "https://lh3.googleusercontent.com/bYCAn3mjgB4ugSY0PL-PCcMBfbvXCSFkzL-pLSIIbZ8sQByQPerHboPQ2fA126K4LDtU",    "https://lh3.googleusercontent.com/u-dX4lpTepsvXs33ds4xxYpApuGS4JBAEb0UsvY_fPbptxnF0QxaKNW0-tJVXaP8a1E",    "https://lh3.googleusercontent.com/qvUz_9IXHQd6FSLUALZo8NKLx-s4uDGyElPOGRsU28TCEficQc0BoNRloRRLqUkH2A",    "https://lh3.googleusercontent.com/tEyGs6MGlY97ccLc4c_HxV9xNOpsvwQyHz6uGAezkVtxm1ydAaTj5EZSUgqlg69qrrk",    "https://lh3.googleusercontent.com/StN0i2BskOs6HCfaPO0DMBOCQMCag3okWVI_SlFJtMytwbgNMBnD5i9hbSqdNlGxffmn",    "https://lh3.googleusercontent.com/GRKqWfo-PLzCKwpgZ8fej4PGsUp1q9eM5a3LQeiYCOW-KUpCOIHXOp3mteZWbJ-pz4My",    "https://lh3.googleusercontent.com/pFQQ_qi8u92duWCNXpEcNKpH2lVpD_hFd5f-UlTP_f6wft3YyYLMzwLitxt-UI6G8vs",    "https://lh3.googleusercontent.com/AoeCU6bT1x0eHRvJwvQyOSKJ31oSayox959qMNVaSzz3uN9bvk1cGek5zyRDe1BdtA",    "https://lh3.googleusercontent.com/vICme1f4J9vFt8wY3xBY-LshGgYyvSbsa4TLJyEtNsy0alUI0i9oMQVq8oJ4l_yR1Aw",    "https://lh3.googleusercontent.com/7sn9m__iVM-peiG6_jkKBuE-QVH_xDaycF_oR1XJlwcAC45ybNZ_Exor09ENOJ41Q2U",    "https://lh3.googleusercontent.com/9I_m2ZXgPtiU4Po4cw_cyIaEpZxynxQ1n3YkhFgakATfbu63a8_f8vGQDxKOHYITzew"  ],  "size": "Varies with device",  "summary": "Task Manager \u2705 Organizer \ud83d\udcc5 Agenda \ud83d\udcdd Daily Reminders \ud83d\udd14 All-in-One Simple App.",  "summaryHTML": "Task Manager \u2705 Organizer \ud83d\udcc5 Agenda \ud83d\udcdd Daily Reminders \ud83d\udd14 All-in-One Simple App.",  "title": "Any.do: To do list, Calendar, Planner & Reminders",  "updated": 1586258773,  "url": "https://play.google.com/store/apps/details?id=com.anydo&hl=en&gl=us",  "version": "Varies with device",  "video": "https://www.youtube.com/embed/2nkllLD0x6o?ps=play&vq=large&rel=0&autohide=1&showinfo=0",  "videoImage": "https://i.ytimg.com/vi/2nkllLD0x6o/hqdefault.jpg" }

This offers a great deal of information, such as the number of ratings, reviews, and ratings for each score (1 to 5). Let's set aside all of that and have a look at their lovely icons:

def format_title(title): sep_index = title.find(':') if title.find(':') != -1 else title.find('-') if sep_index != -1: title = title[:sep_index] return title[:10] fig, axs = plt.subplots(2, len(app_infos) // 2, figsize=(14, 5)) for i, ax in enumerate(axs.flat):    ai = app_infos[i]    img = plt.imread(ai['icon'])    ax.imshow(img)    ax.set_title(format_title(ai['title']))    ax.axis('off')

We can save the app information for later by converting the JSON objects into a Pandas data frame and saving the output to a CSV file:

app_infos_df = pd.DataFrame(app_infos) app_infos_df.to_csv('apps.csv', index=None, header=True)

Scraping App Reviews

You may use the scraping tool to create a balanced dataset by filtering the review score. And, to receive a sample of evaluations for each app, you may arrange the reviews by how helpful they are, which Google Play considers to be the most essential factor.

We're looking for:

A well-balanced dataset — each score (1–5) has nearly the same number of reviews.

A representative sample of each app's reviews

You may achieve the first criterion by utilizing the scrape package option to filter the review score. For the second, we'll sort the reviews by helpfulness, which suggests which are the most important to Google Play. Just in case, we'll get a subset from the most recent:

app_reviews = [] for ap in tqdm(app_packages):  for score in list(range(1, 6)):    for sort_order in [Sort.MOST_RELEVANT, Sort.NEWEST]:      rvs, _ = reviews(        ap,        lang='en',        country='us',        sort=sort_order,        count= 200 if score == 3 else 100,        filter_score_with=score      )      for r in rvs:        r['sortOrder'] = 'most_relevant' if sort_order == Sort.MOST_RELEVANT else 'newest'        r['appId'] = ap      app_reviews.extend(rvs)

Each review includes the app's id and sort order. Consider the following as an example:

print_json(app_reviews[0]) {  "appId": "com.anydo",  "at": "2020-04-05 22:25:57",  "content": "Update: After getting a response from the developer I would change my rating to 0 stars if possible. These guys hide behind confusing and opaque terms and refuse to budge at all. I'm so annoyed that my money has been lost to them! Really terrible customer experience. Original: Be very careful when signing up for a free trial of this app. If you happen to go over they automatically charge you for a full years subscription and refuse to refund. Terrible customer experience and the app is just OK.",  "repliedAt": "2020-04-07 14:09:03",  "replyContent": "Our policy and TOS are completely transparent and can be found in the Help Center and our main page. In addition, payment can only be made upon the user's authorization via the app and Google Play. We provide users with a full 7 days trial to test the app with an additional 48 hours for a refund, along with priority support for all issues.",  "reviewCreatedVersion": "4.17.0.3",  "score": 1,  "sortOrder": "most_relevant",  "thumbsUpCount": 37,  "userImage": "https://lh3.googleusercontent.com/a-/AOh14GiHdfNEu1DwwcJ6yNyju8Yvn4JwjpzuXvD74aVmDA",  "userName": "Andrew Thomas" }

repliedAt and replyContent are the developer's answer to the review is included in the content which can be sometimes found missing.

len(app_reviews)

How Many Reviews will you receive?

len(app_reviews) 15750 Save the reviews to CSV files app_reviews_df = pd.DataFrame(app_reviews) app_reviews_df.to_csv('reviews.csv', index=None, header=True)

Summary

We now have over 15K user reviews from 15 different productivity apps.

Scripting with Pytorch is used to run the code (Google Colab)

Installing required packages and configuring imports

You learned how to:

Define the goals and expectations for your dataset.

Google Play app information can be scraped.

Google Play app user reviews can be scraped.

Save the data as a CSV file.

Following that, we'll use BERT to analyze the reviews for the sentiment.

Are you looking for a way to harvest reviews from Google Play?

Scraping Product Reviews Data

Extracting product reviews data from e-commerce websites has become amongst the most important competitive intelligence actions in as well as around an e-commerce space. Scraping e-commerce product reviews is a wonderful source of neutral reviews organically given by real consumers. It means that as a manufacturer if you want to collect deeper insights about the products, you should search for e-commerce product reviews pages. Whereas the accessibility of product reviews on different e-commerce websites is huge and deep, not all companies have the infrastructure, resources, and expertise of crawling and scraping reviews from e-commerce websites in an automatic manner.

Fortunately, Reviewgators specializes in big-scale web data scraping solutions as well as can assist you in extracting e-commerce product reviews from different e-commerce portals. Our well-managed web scraping services come with end-to-end crawler management that might insulate from the shades of web extraction activities as well as help you concentrate on the applications of delivered data.

Quick Product Review Scraping Implementation

At Reviewgators, we can assist you in quickly implementing product reviews scraping in a shorter time. Our key focus is quality data and speed implementation. Reviewgators can fulfill your customized and big-scale requirements on composite sites without coding in the shortest possible time. We offer ready-to-utilize product reviews scraping services because of our huge experience in creating big-scale web scrapers for different clients across various verticals. We have an amazing customer support team for understanding every customer’s requirements as well as helping them go live in record time.

Different Applications of E-commerce Product Review Scraping

E-commerce is taking the whole world by storm as well as there are no scarcities of product reviews on e-commerce portals. The key benefit to manufacturing companies is an unbiased nature of reviews that will assist them in understanding their consumers to serve better. Let’s go through the most general applications of product review scraping.

Understand Customer Preferences:

To stay updated with customers’ preferences is important for successful products. In case, your products aren’t addressing what consumers want, you are having money on a table as well as contributing to customer dissatisfaction. For avoiding that, you need to understand the needs and demands of the targeted customers. By scraping product reviews data as well as analyzing that with the right goals, the business can recognize the important factors, which are getting sales in the niche as well as tweak products consequently.

Brand Monitoring:

Brand image or reputation is an enormous factor when comes to consumer loyalty as well as business growth for all organizations. Keeping a positive brand image is important and it means your business needs to be all ears with customers’ complaints. Brand monitoring could help you find unaddressed problems of customers, which can increase to bigger problems if not noticed early on. Extracting reviews from different e-commerce websites can assist you to monitor as well as preserve the brand image positively.

Competitor Analysis:

Taking note of your customers is just not sufficient to deal with this very competitive business these days. At times, data related to competitors can assist you to find lower-hanging fruits that you could leverage before doing. For instance, in case, reviews on competitors’ products suggest the demands for any particular features, be the first to include them in your product. It would assist you in staying ahead in the curve as well as gathering more users.

Natural Language Processing (NLP):

Natural language processing enables machines to know the context after human languages. Different systems produced using NLP assists in running voice assistant platforms including Cortana, Siri, and Google Now, and translation services as well as Artificial Intelligence Systems. An enormous amount of data is a must-have to deal with the NLP system requirements. As product reviews extracted from e-commerce websites are user-generated content, this makes for ideal data for training NLP systems.

Fraud Recognition:

Fake products have always become a threat for brands. They will affect the sales figures as well as leave bad impressions amongst customers that might never realize faulty products they got were fake. Extracting product reviews assists you in accessing the data that might have suggestions about ongoing frauds. Live crawls or real-time crawls could be done to recognize e-commerce partners that don’t stick with the agreement.

How Does Scraping Product Reviews Work?

TripAdvisor reviews have many useful details about hotel and flight prices, which can assist you in increasing your business. Also, it is home to tons of helpful stats about common travel destinations, restaurants, and hotels.

If you wish to scrape and utilize all the data, you could use data scraping to automatically scrape data from TripAdvisor reviews. Scraping data involves the use of automated bots for collecting data from a website’s HTML version as well as deliver collected data in CSV or Excel format, therefore you can analyze, process, as well as use this data.

Using an API (Application Programming Interface) or an HTML module, you can get the required quickly and smoothly. and quickly. Read this blog and learn about why these TripAdvisor reviews are so important, what web scraping is, as well as how you can extract reviews data from TripAdvisor using an HTML module or an API. We’ll also understand how to utilize ReviewGators’ HTML scraper and API.

Why TripAdvisor Reviews Are So Important

How many reviews TripAdvisor website has? In 2020, TripAdvisor had more than 884 million reviews about accommodations, hotels, and more.

It means TripAdvisor reviews could tell us so much about facilities, experiences, flights, as well as other things that can assist consumers:

Avoid general tourist traps or mistakes

Determine new places, experiences, and accommodations

Get in-depth research for travel destinations

Have a superior understanding of the most loved and the most hated tourist attractions in the particular area

For example, if you want to visit Seattle for your weekend holidays, you can utilize scraping to find out which neighboring city is economical. Similarly, you may use scraping for spotting and avoiding general mistakes that travelers make while touring any particular area.

You need to think about going through TripAdvisor reviews in case, you’re a tourism and Travel Company as this will assist you:

Know the reputation of your travel facility as well as find space for development. If you’re having a visit of local winegrowers, a breakfast or bed, a hotel, or a motel, Scraping TripAdvisor Reviews Data will offer you a sense of how the public sees the facility.

Understand the travel industry’s present trends as well as how you could catch up as well as show up from the competitors.

How Can Web Scraping Help You Get Data From the TripAdvisor Reviews?

Web scraping is the finest way of accessing and using a huge amount of data given in TripAdvisor reviews. A web scraper will assist you to compile as well as transfer data in the spreadsheet to do review and analysis.

Conventionally, you would need to get through all TripAdvisor reviews as well as manually input various parameters in the spreadsheet. For instance, while reading a TripAdvisor review given below, you might note in Excel that:

This is a five-star review

This was reviewed on 5th February 2020

This was posted with the mobile phone

Its writer had visited the location during February 2020

One person had found the review useful

Review Scraping from TripAdvisor Using an API

An API is the software interface, which connects various computer programs as well as permits them to move data without revealing the code underlying every data transfer.

APIs help you to scrape as well as isolate data categories so that you don’t need to examine a huge amount of data within your database. That is how you could find reviews on TripAdvisor as well as how you could get the latest reviews on the TripAdvisor website. You may also utilize code to direct API to give commands to the scraping software for scraping particular data categories from pages you need when you aren’t using your computer. It will help you keep dataset statistics, which are always shifting including stock market pricing.

Though APIs look complex, extracting TripAdvisor reviews having an API could be extremely simple.

Let’s get started:

Download as well as install data scraping software. Ensure that you know the software documentation before installing it. However, note that a few APIs like ReviewGators API, are browser-based so you don’t need to download them.

Visit any web page you need to scrape.

Copy its URL.

Paste that URL in the program.

Then, get the complete HTML output in seconds.

The majority of data scraping tools have the extraction sequence for various HTML elements given on any page. For example, most extraction tools scrape the text initially. Then, you can choose other scrapped categories like Class Attribute, Inner HTML, Captcha, JSON object, href attribute, as well as complete HTML. Accessible categories rely on which data scraping tool you use. So, ensure that you have the right data scraping tool for what you wish to achieve.

ReviewGators’ API simplifies this procedure by providing you with all the HTML categories after pressing the “run” button.

After getting complete output, you can export data to the desired analysis program like SPSS, XLSTAT, and Graphpad.

How to Extract TripAdvisor Reviews Using an HTML Module?

Although it’s suggested that you understand how to do coding before using the APIs, in case, you don’t do coding, you can still extract TripAdvisor reviews with ReviewGators’ pre-made HTML module.

To do scraping with the HTML module:

Visit ReviewGators’ HTML scraper that will help you collect all kinds of HTML info from any website.

Copy the page URL you wish to extract and paste that into the URL field.

With the CSS selector’s field, paste CSS selectors and look for the elements to scrape.

Under the XPath field, just paste your XPath as it will help you compute the values or choose notes from the HTML document. Just play around with XPath expressions for scraping web data.

Press the “start scraping” tab after checking the “I’m not a robot” option. You will get HTML versions of URLs you have pasted in the CSV format. Like ReviewGators API, the HTML scraper helps you to get all HTML categories data.

Download a CSV file or get it directly into your database.

In case, you wish to extract multiple pages, just click the “add one more row” tab at the bottom to add around 10 scrapes at one time.

Conclusion