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      Different voices between Airbnb and hotel customers: An integrated analysis of online reviews using structural topic model

      , , ,
      Journal of Hospitality and Tourism Management
      Elsevier BV

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          Causal Inference without Balance Checking: Coarsened Exact Matching

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            VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text

            The inherent nature of social media content poses serious challenges to practical applications of sentiment analysis. We present VADER, a simple rule-based model for general sentiment analysis, and compare its effectiveness to eleven typical state-of-practice benchmarks including LIWC, ANEW, the General Inquirer, SentiWordNet, and machine learning oriented techniques relying on Naive Bayes, Maximum Entropy, and Support Vector Machine (SVM) algorithms. Using a combination of qualitative and quantitative methods, we first construct and empirically validate a gold-standard list of lexical features (along with their associated sentiment intensity measures) which are specifically attuned to sentiment in microblog-like contexts. We then combine these lexical features with consideration for five general rules that embody grammatical and syntactical conventions for expressing and emphasizing sentiment intensity. Interestingly, using our parsimonious rule-based model to assess the sentiment of tweets, we find that VADER outperforms individual human raters (F1 Classification Accuracy = 0.96 and 0.84, respectively), and generalizes more favorably across contexts than any of our benchmarks.
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              The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry

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                Author and article information

                Contributors
                Journal
                Journal of Hospitality and Tourism Management
                Journal of Hospitality and Tourism Management
                Elsevier BV
                14476770
                June 2022
                June 2022
                : 51
                : 119-131
                Article
                10.1016/j.jhtm.2022.03.004
                214ffd64-eed0-4720-98f9-407be329768c
                © 2022

                https://www.elsevier.com/tdm/userlicense/1.0/

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