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| تعداد نشریات | 162 |
| تعداد شماره‌ها | 6,578 |
| تعداد مقالات | 71,072 |
| تعداد مشاهده مقاله | 125,685,080 |
| تعداد دریافت فایل اصل مقاله | 98,914,571 |
ارائه روش هوشمند وب کاوی (خزش) برای تحلیل نظرات برخط استفاده کنندگان از اقامتگاه های شهر تهران | ||
| نشریه گردشگری شهری | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 26 دی 1403 | ||
| نوع مقاله: مقاله مستخرج از رساله دکتری | ||
| شناسه دیجیتال (DOI): 10.22059/jut.2025.378415.1221 | ||
| نویسندگان | ||
| حسنعلی فرجی سبکبار* 1؛ احمد پوراحمد2؛ سعید زنگنه شهرکی3؛ اطهره عیاشی4؛ فابیو کربونه5 | ||
| 1دانشکده جغرافیا | ||
| 2استاددانشگاه تهران | ||
| 3استادیار دانشگاه تهران | ||
| 4دانشگاه تهران | ||
| 5دانشگاه نورثهمپتون | ||
| چکیده | ||
| امروزه، صنعت گردشگری به طور فزاینده ای به نظرات آنلاین کاربران برای ارتقا خدمات و جذب مشتریان جدید وابسته است، به طوری که نظرات و تجربیات آنلاین گردشگران اهمیت ویژه ای دارد و پتانسیل های این روش، بینش های ارزشمندی را برای این بخش برجسته می کند.. از طرفی، حجم داده های زیاد و بزرگ موجود در واب سایت های رزرو اقامتگاه، جمع آوری و تحلیل را به صورت دستی دشوار و زمان بر می کند. از این رو در این مقاله، به بررسی یک روش جامع خودکار وب کاوی برای جمع آوری و تجزیه و تحلیل نظرات کاربران در یکی از سایت های آنلاین اقامتگاه در شهر تهران ارائه شده است. این روش هوشمند شامل مراحلی مانند انتخاب وب سایت، بررسی ابزارها، استخراج داده ها، پیش پردازش و تجزیه و تحلیل نظرات است. با استفاده از این روش، صاحبان اقامتگاه ها، مدیران و بازاریابان می توانند بینشی عمیق درباره ترجیحات مشتریان، سطح رضایت و نیازهای بهبود را به دست آورند. هم چنین گردشگران و کاربران برای انتخاب اقامتگاه خود می توانند اطلاعات ارزشمندی از تجربیات سایرین کسب نمایند. بر اساس نتایج تحقیق، روش هوشمند وب کاوی، امکان تحلیل داده های بزرگ و ارزشمند را فراهم می کند و می تواند به تصمیم گیری های استراتژِیک در حوزه خدمات گردشگری کمک کند. یافته‌ها با استفاده از آمار توصیفی و آزمون‌های تحلیلی شامل آزمون‌های t و ANOVA، برای ارزیابی میانگین تفاوت در نظرات کاربران در دسته‌های مختلف هتل ارائه شده‌اند. این مطالعه نشان می‌دهد که میانگین امتیازات امکانات هتل، قیمت اتاق، کیفیت اتاق، موقعیت هتل و پروتکل‌های بهداشتی عموماً بالاتر از میانگین مورد انتظار است که نشان‌دهنده درک کلی مثبت از هتل‌های تهران است. | ||
| کلیدواژه‌ها | ||
| خزش وب؛ گردشگری تهران؛ سلنیوم؛ تحلیل آنلاین نظرات | ||
| عنوان مقاله [English] | ||
| Introducing an Intelligent Web Scraping(Mining) Method for Analyzing Online Reviews of Tehran Accommodation Users | ||
| نویسندگان [English] | ||
| Hassan Ali Faraji Sabokbar1؛ Ahmad Porahmad2؛ saeed zanganeh3؛ Athare Ayashi4؛ Fabio Carbone5 | ||
| 1Faculty of Geography | ||
| 2Ffaculty of Geography | ||
| 3Assistant Professor at Tehran University | ||
| 4University of Tehran | ||
| 5Senior Lecturer in Tourism Management & Marketing, University of Northampton, Events, Tourism & Hospitality | ||
| چکیده [English] | ||
| In the age of digital information and online platforms, the tourism and hospitality industry has seen significant changes in expressing opinions and sharing customer experiences. So that the awareness decision of choosing travel, destination and accommodation relies heavily on online reviews by tourists, so that online reviews have become an essential resource for tourists who are looking for a suitable travel experience and accommodation. Considering the importance of these opinions and experiences in tourists' decision-making, and that these opinions contain a large amount of data and their manual analysis is impractical, the method of intelligent web mining in online accommodation platforms Tourism has been used. Web mining is a process that comes from creating a computer program to download, analyze and organize data from web pages in an automated way and is very useful for extracting data from multiple pages simultaneously. In the next step, this article examines the steps and processes involved in web mining. The steps include 1- site analysis 2- web mining 3- data extraction 4- data organization, processing and storage. This article has used Selenium library tools for web mining. Selenium is a powerful and popular web mining tool that provides a framework for automating web browsers. In fact, Selenium is a tool for web mining of dynamic pages and it allows interaction with web pages and actions such as clicking buttons or filling forms and extracting data from websites. The first step is to install Selenium, and the corresponding codes are written in the Python environment as follows. After that, finding the profile URLs of each of the residences is done using the WebDriver command from the Selenium library, and then automating the click on each of the URLs. The next step is finding and moving among the tags and elements inside the URLs, which is done with the XPath command. In the last step, after identifying all the tags and classes in the site's HTML source code, the for loop is used to extract all the tags and elements of all the pages and store it in an Excel file from the pandas library in Python. is used The findings of the paper, presented using descriptive statistics and analytical tests, show that the average scores for various aspects of the hotel, such as facilities, room price, quality, location, and hygiene protocols, are generally higher than the expected average, indicating an overall positive perception of the hotel. Tehran hotels. Finally, the article emphasizes that web mining, as a powerful technique for automatically collecting data from websites, can significantly help improve tourism services and strategic decisions in this area. By studying and analyzing these opinions, it is possible to better understand the needs and preferences of tourists and make the necessary improvements in the accommodations. In this paper, we present a comprehensive automated web scraping method for collecting and analyzing user reviews on an online accommodation booking platform in Tehran, Iran. This intelligent method involves several steps, including website selection, tool assessment, data extraction, preprocessing, and review analysis. By employing this method, accommodation owners, managers, and marketers can gain deep insights into customer preferences, satisfaction levels, and areas for improvement. Additionally, tourists and users can obtain valuable information from the experiences of others to guide their accommodation choices. The proposed intelligent web scraping method facilitates the analysis of large and valuable data sets, which can inform strategic decision-making in the tourism industry. The findings are presented using descriptive statistics and analytical tests, including t-tests and ANOVA, to evaluate the mean differences in user reviews across various hotel categories. The study demonstrates that the average ratings for hotel facilities, room prices, room quality, hotel location, and health protocols are generally above the expected mean, indicating an overall positive perception of Tehran hotels. Key Points: Automated Web Scraping for User Review Analysis: The study introduces an automated web scraping method to gather and analyze user reviews from an online accommodation platform. Benefits for Accommodation Stakeholders: The method provides valuable insights for accommodation owners, managers, and marketers to understand customer preferences and improve services. Information for Tourists and Users: Tourists and users can benefit from the extracted reviews to make informed accommodation choices. Analysis of Large and Valuable Data: The method enables the analysis of large volumes of user review data, facilitating strategic decision-making in the tourism industry. Positive Perception of Tehran Hotels: The findings indicate a generally positive perception of Tehran hotels based on user reviews of facilities, prices, quality, location, and health protocols.Overall, the study contributes to the field of tourism research by demonstrating the effectiveness of web scraping for analyzing user reviews and providing valuable insights for both industry stakeholders and consumers. Below are some of the effects of these analyzes of automatic web mining methods for businesses and users: 1- Improving the quality of services 2- Better decision-making by users 3- Marketing strategies 4- Improving trust in business | ||
| کلیدواژه‌ها [English] | ||
| Web Scraping, selenium, Tehran Tourism, Online review analysis | ||
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آمار تعداد مشاهده مقاله: 44 |
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