The total number of reviews and ratings on Tripadvisor worldwide has increased significantly since 2014, reaching the one billion mark in 2021. In the following years, the company mentioned that the number of reviews on the platform exceeded one billion. As of 2024, such reviews and ratings related to over nine million travel entries, including experiences, accommodation, restaurants, airlines, and cruises.

There are many contexts where dyadic data are present. In social networks, users are linked to a variety of items, defining interactions. In the social platform of TripAdvisor, users are linked to restaurants by means of reviews posted by them. Using the information of these interactions, we can get valuable insights for forecasting, proposing tasks related to recommender systems, sentiment analysis, text-based personalisation or text summarisation, among others. Furthermore, in the context of TripAdvisor there is a scarcity of public datasets and lack of well-known benchmarks for model assessment.

We present six new TripAdvisor datasets from the restaurants of six different cities: London, New York, New Delhi, Paris, Barcelona and Madrid.

If you use this data, please cite the following paper under submission process (preprint - arXiv)

We exclusively collected the reviews written in English from the restaurants of each city. The tabular data is comprised of a set of six different CSV files, containing numerical, categorical and text features:

• parse_count: numerical (integer), corresponding number of extracted review by the web scraper (auto-incremental)
• author_id: categorical (string), univocal, incremental and anonymous identifier of the user (UID_XXXXXXXXXX)
• restaurant_name: categorical (string), name of the restaurant matching the review
• rating_review: numerical (integer), review score in the range 1-5
• sample: categorical (string), indicating “positive” sample for scores 4-5 and “negative” for scores 1-3
• review_id: categorical (string), univocal and internal identifier of the review (review_XXXXXXXXX)
• title_review: text, review title
• review_preview: text, preview of the review, truncated in the website when the text is very long
• review_full: text, complete review
• date: timestamp, publication date of the review in the format (day, month, year)
• city: categorical (string), city of the restaurant which the review was written for
• url_restaurant: text, restaurant url

In 2024, Tripadvisor Inc.'s business segment Brand Tripadvisor recorded an eight percent annual decline in revenue. That year, earnings from Tripadvisor's flagship brand – including revenue from Tripadvisor-branded hotels, media and advertising, experiences and dining – amounted to 949 million U.S. dollars. In 2024, Tripadvisor's revenue worldwide exceeded 1.8 billion U.S. dollars overall. How popular is Tripadvisor's website? In 2025, tripadvisor.com, the global website of Tripadvisor Inc.'s leading brand, was one of the most visited travel and tourism websites worldwide, ranking ahead of other popular web pages like airbnb.com and expedia.com. Breaking down tripadvisor.com's online traffic by country shows that the United States accounted for almost half of total website visits that year. Viator's app is on the rise From 2020 to 2024, Viator, a company focusing on travel experiences and activities, was Tripadvisor's brand that recorded the highest increase in revenue. In 2024, the number of aggregated downloads of the Viator app worldwide grew sharply over the previous year, exceeding four million.

TripAdvisor reported $411M in Operating Expenses for its fiscal quarter ending in December of 2024. Data for TripAdvisor | TRIP - Operating Expenses including historical, tables and charts were last updated by Trading Economics this last March in 2025.

TripAdvisor hotel review dataset, hotel links and hotel data. The user reviews and hotel basic information data from the hotel introduction pages of the three important cities of Shanghai, London and New York in the TripAdvisor hotel section are crawled in order of ranking, including more than 60,000 reviews from more than 100 hotels.

An English corpus for studying local sentiment flows and aspect-based sentiment analysis. It contains 2100 hotel reviews balanced with respect to the reviews’ sentiment scores. All reviews are segmented into subsentence-level statements that have then been manually classified as a fact, a positive, or a negative opinion. Also, all hotel aspects mentioned in the reviews have been annotated as such:arguana-tripadvisor-annotated-plus-software-v1.ziparguana-tripadvisor-annotated-v2.zipIn addition, we provide nearly 200k further hotel reviews without manual annotations:v1 upon requestarguana-tripadvisor-unannotated-v2.zip. The corpus is free-to-use for scientific purposes, not for commercial applications. In version 2, the annotated XMI files have been changed according to a new underlying type system that is more easily extendable. Notice that some adaptations of the software of version 1 are necessary to make it work with version 2.In case you publish any results related to the ArguAna TripAdvisor corpus, please cite our CICLing 2014 paper.

In January 2025, most visits to the travel and tourism website tripadvisor.com came from the United States. During that month, website visits from the U.S. accounted for almost 48 percent of total visits to Tripadvisor's web page. In 2025, tripadvisor.com was one of the most visited travel and tourism websites worldwide.

TripAdvisor reported $11M in Interest Expense on Debt for its fiscal quarter ending in December of 2024. Data for TripAdvisor | TRIP - Interest Expense On Debt including historical, tables and charts were last updated by Trading Economics this last March in 2025.

TripAdvisor 市值 - 当前值，历史数据，预测，统计，图表和经济日历 - Mar 2025.Data for TripAdvisor | 市值 including historical, tables and charts were last updated by Trading Economics this last March in 2025.

TripAdvisor Salg - Gjeldende verdier, historiske data, prognoser, statistikk, diagrammer og økonomiske kalender - Mar 2025.Data for TripAdvisor | Salg including historical, tables and charts were last updated by Trading Economics this last March in 2025.

A. Market Research and Analysis: Utilize the Tripadvisor dataset to conduct in-depth market research and analysis in the travel and hospitality industry. Identify emerging trends, popular destinations, and customer preferences. Gain a competitive edge by understanding your target audience's needs and expectations.

B. Competitor Analysis: Compare and contrast your hotel or travel services with competitors on Tripadvisor. Analyze their ratings, customer reviews, and performance metrics to identify strengths and weaknesses. Use these insights to enhance your offerings and stand out in the market.

C. Reputation Management: Monitor and manage your hotel's online reputation effectively. Track and analyze customer reviews and ratings on Tripadvisor to identify improvement areas and promptly address negative feedback. Positive reviews can be leveraged for marketing and branding purposes.

D. Pricing and Revenue Optimization: Leverage the Tripadvisor dataset to analyze pricing strategies and revenue trends in the hospitality sector. Understand seasonal demand fluctuations, pricing patterns, and revenue optimization opportunities to maximize your hotel's profitability.

E. Customer Sentiment Analysis: Conduct sentiment analysis on Tripadvisor reviews to gauge customer satisfaction and sentiment towards your hotel or travel service. Use this information to improve guest experiences, address pain points, and enhance overall customer satisfaction.

F. Content Marketing and SEO: Create compelling content for your hotel or travel website based on the popular keywords, topics, and interests identified in the Tripadvisor dataset. Optimize your content to improve search engine rankings and attract more potential guests.

G. Personalized Marketing Campaigns: Use the data to segment your target audience based on preferences, travel habits, and demographics. Develop personalized marketing campaigns that resonate with different customer segments, resulting in higher engagement and conversions.

H. Investment and Expansion Decisions: Access historical and real-time data on hotel performance and market dynamics from Tripadvisor. Utilize this information to make data-driven investment decisions, identify potential areas for expansion, and assess the feasibility of new ventures.

I. Predictive Analytics: Utilize the dataset to build predictive models that forecast future trends in the travel industry. Anticipate demand fluctuations, understand customer behavior, and make proactive decisions to stay ahead of the competition.

J. Business Intelligence Dashboards: Create interactive and insightful dashboards that visualize key performance metrics from the Tripadvisor dataset. These dashboards can help executives and stakeholders get a quick overview of the hotel's performance and make data-driven decisions.

Incorporating the Tripadvisor dataset into your business processes will enhance your understanding of the travel market, facilitate data-driven decision-making, and provide valuable insights to drive success in the competitive hospitality industry

Liberty TripAdvisor 流动资产 - 当前值，历史数据，预测，统计，图表和经济日历 - Mar 2025.Data for Liberty TripAdvisor | 流动资产 including historical, tables and charts were last updated by Trading Economics this last March in 2025.

Dataset

This dataset was created by Rifki Andriyanto

Released under MIT

Contents

TripAdvisor Passività Correnti - Valori correnti, dati storici, previsioni, statistiche, grafici e calendario economico - Mar 2025.Data for TripAdvisor | Passività Correnti including historical, tables and charts were last updated by Trading Economics this last March in 2025.

TripAdvisor Varlıklar - Akım değerleri, tarihsel veriler, tahminler, istatistikler, grafikler ve ekonomik takvim - Mar 2025.Data for TripAdvisor | Varlıklar including historical, tables and charts were last updated by Trading Economics this last March in 2025.

In February 2025, the number of visits to the travel and tourism website tripadvisor.com declined over the previous month, totaling roughly 120 million. In 2025, tripadvisor.com was one of the most visited travel and tourism websites worldwide.

TripAdvisor reported $2.11B in Market Capitalization this March of 2025, considering the latest stock price and the number of outstanding shares.Data for TripAdvisor | TRIP - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last March in 2025.

The number of Tripadvisor, Inc.'s employees worldwide grew slightly in 2024 over the previous year, reaching 2,860. Despite the annual increase, the company's headcount remained below pre-pandemic levels. Tripadvisor’s revenue and marketing expenses In 2024, Tripadvisor's revenue reached the company's highest figure to date, exceeding 1.8 billion U.S. dollars. With the increase in revenue, Tripadvisor's marketing expenses also reached a peak that year, amounting to over 700 million U.S. dollars. How popular is Tripadvisor's website? In a list of the most visited travel and tourism websites worldwide in 2025, tripadvisor.com, the global web page of Tripadvisor, Inc.'s flagship brand, ranked second, ahead of other popular sites like airbnb.com and trip.com. That year, booking.com, the leading brand of Booking Holdings, was the most visited global travel and tourism website.

TripAdvisor - ارزش های فعلی، داده های تاریخی، پیش بینی، آمار، نمودار و تقویم اقتصادی - Feb 2025.Data for TripAdvisor including historical, tables and charts were last updated by Trading Economics this last February in 2025.

Explore the historical Whois records related to tripadvisor.in (Domain). Get insights into ownership history and changes over time.