1,720,974 research outputs found
Estimating the dose-response function through a GLM approach
No full textAbstract. In this article, we revise the estimation of the dose–response function described in Hirano and Imbens (2004, Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives, 73–84) by proposing a flexible way to estimate the generalized propensity score when the treatment variable is not necessarily normally distributed. We also provide a set of programs that accomplish this task. To do this, in the existing doseresponse program (Bia and Mattei, 2008, Stata Journal 8: 354–373), we substitute the maximum likelihood estimator in the first step of the computation with the more flexible generalized linear model
Forecasting Tourism Demand through Social Network and Semantic Analysis of Online Big Data
No full textForecasting Tourism Demand through Social Network and Semantic Analysis of Online Big Data
No full textUsing social network and semantic analysis to analyze online travel forums and forecast tourism demand
No full textForecasting tourism demand has important implications for both policy makers and companies operating in the tourism industry. In this research, we applied methods and tools of social network and semantic analysis to study user-generated content retrieved from online communities which interacted on the TripAdvisor travel forum. We analyzed the forums of 7 major European capital cities, over a period of 10 years, collecting more than 2,660,000 posts, written by about 147,000 users. We present a new methodology of analysis of tourism-related big data and a set of variables which could be integrated into traditional forecasting models. We implemented Factor Augmented Autoregressive and Bridge models with social network and semantic variables which often led to a better forecasting performance than univariate models and models based on Google Trend data. Forum language complexity and the centralization of the communication network – i.e. the presence of eminent contributors – were the variables that contributed more to the forecasting of international airport arrivals
Factor augmented bridge models (FABM) and soft indicators to forecast italian industrial production
No full textThis paper presents a new forecasting approach straddling the conventional methods applied to the Italian industrial
production index. Specifically, the proposedmethod treats factormodels and bridge models as complementary ingredients
feeding a unique model specification. We document that the proposed approach improves upon traditional bridge models
bymaking efficient use of the information conveyed by a large amount of survey data onmanufacturing activity. Different
factor algorithms are compared and, under the provision that a large estimation window is used, partial least squares
outperform principal component-based alternatives
Brand Intelligence in the Era of Big Data: Advances in the Use of the Semantic Brand Score
No full textBrand Intelligence in the Era of Big Data: Advances in the Use of the Semantic Brand Score
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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