Can We Predict Your Sentiments by Listening to Your Peers?
Published 1 January 2016
Julia Neidhardt, Nataliia Rümmele, Hannes Werthner
Citations7
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
The emotions of the users regarding their forthcoming trips are studied with the objective to characterize interdependencies between them and some evidence that social influence between the users in the network exists is provided.
Abstract
Web sources of tourism services provide valuable resources of knowledge not only for the travellers but also for the companies. Tourism operators are increasingly aware that user related data should be regarded as an important asset. In this paper, user activities and interactions in the tourism domain are analysed. In particular, the emotions of the users regarding their forthcoming trips are studied with the objective to characterize interdependencies between them. Social network analysis is applied to characterize the interactions between the users. To capture their emotions, text mining techniques and sentiment analysis are applied to construct a measure, which is based on free-text comments in a travel forum. The experimental outcome provides some evidence that social influence between the users in the network exists.
Keywords
Computer Science
Maximizing the spread of influence through a social network
7,314 Citations2003David Kempe, Jon Kleinberg +1 more
An analysis framework based on submodular functions shows that a natural greedy strategy obtains a solution that is provably within 63% of optimal for several classes of models, and suggests a general approach for reasoning about the performance guarantees of algorithms for these types of influence problems in social networks.
CERN Document Server (European Organization for Nuclear Research)Natural Language Processing with Python
3,449 Citations2009Steven Bird, Ewan Klein +1 more
Computational LinguisticsLexicon-Based Methods for Sentiment Analysis
3,255 Citations2011Maite Taboada, Julian Brooke +3 more
The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic orientation (polarity and strength), and incorporates intensification and negation, and is applied to the polarity classification task.
SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining.
2,652 Citations2010Stefano Baccianella, Andrea Esuli +1 more
This work discusses SENTIWORDNET 3.0, a lexical resource explicitly devised for supporting sentiment classification and opinion mining applications, and reports on the improvements concerning aspect (b) that it embodies with respect to version 1.0.
SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining
2,489 Citations2006Andrea Esuli, Fabrizio Sebastiani
SENTIWORDNET is a lexical resource in which each WORDNET synset is associated to three numerical scores Obj, Pos and Neg, describing how objective, positive, and negative the terms contained in the synset are.
Sociological Methodology8. Dynamic Networks and Behavior: Separating Selection from Influence
991 Citations2010Christian Steglich, Tom A. B. Snijders +1 more
Cambridge University Press eBooksExponential Random Graph Models for Social Networks
829 Citations2012Dean Lusher, Johan Koskinen +1 more
Modelling social networks: the dual importance of who you know and where you live Galina Daraganova and Philippa Pattison and Philippa Pattison and Modelling social networks: next steps.
Expertise networks in online communities
795 Citations2007Jun Zhang, Mark S. Ackerman +1 more
This study analyzes the Java Forum, a large online help-seeking community, using social network analysis methods and tests a set of network-based ranking algorithms on this large size social network in order to identify users with high expertise.
Social NetworksModeling social influence through network autocorrelation: constructing the weight matrix
596 Citations2002Roger Leenders
How social influence processes can be incorporated in the specification of W, the elements of which represent the influence pattern present in the network, is discussed and a series of operationalizations of W is discussed.
Information and Communication Technologies in Tourism 2011
344 Citations2011Rob Law, Matthias Fuchs +1 more
Information and Communication Technologies in Tourism 2011 : Proceedings of the International Conference in Innsbruck, Austria, January 26–28, 2011.
Journal of Business ResearchAnalyzing destination branding and image from online sources: A web content mining approach
246 Citations2015Clemens Költringer, Astrid Dickinger
This study presents an automated web content mining approach and demonstrates how to extract destination brand identity and image through web contentmining.
PLoS ONEAnger Is More Influential than Joy: Sentiment Correlation in Weibo
233 Citations2014Rui Fan, Jichang Zhao +2 more
It is found that the correlation of anger among users is significantly higher than that of joy, and there is a stronger sentiment correlation between a pair of users if they share more interactions.
Research Methods in Social Network Analysis
229 Citations2017Linton C. Freeman
A Survey of Models and Algorithms for Social Influence Analysis
198 Citations2011Jimeng Sun, Jie Tang
This chapter surveys the research on social influence analysis with a focus on the computational aspects, and presents the researchOn social influence maximization which has many practical applications including marketing and advertisement.
Physica A Statistical Mechanics and its ApplicationsNegative emotions boost user activity at BBC forum
163 Citations2011Anna Chmiel, Paweł Sobkowicz +5 more
An empirical study of user activity in online BBC discussion forums, measured by the number of posts written by individual debaters and the average sentiment of these posts, shows that most posts contain negative emotions and the most active users in individual threads express predominantly negative sentiments.
Information Technology & TourismFuture research issues in IT and tourism
153 Citations2015Hannes Werthner, Aurkene Alzua-Sorzabal +11 more
This manifesto provides guidelines on strategic research issues for the research community, but as such it is also conceived as a basis document for industry and policy makers.
Classification of Customer Reviews based on Sentiment Analysis
133 Citations2012Dietmar Gräbner, Markus Zanker +2 more
The evaluation of the classification on test data shows that the proposed system performs better compared to a predefined baseline: if a customer review is classified as good or bad the classification is correct with a probability of about 90%.
Cambridge University Press eBooksExponential Random Graph Models for Social Networks
128 Citations2013Johan Koskinen, Tom A. B. Snijders
The chapters in this edited volume provide the theoretical and methodological underpinnings of ERGMs, including models for univariate, multivariate, bipartite, longitudinal, and social influence–type ERG Ms, and each method is applied in individual case studies illustrating how social science theories may be examined empirically using ERGs.
Proceedings of the International AAAI Conference on Web and Social MediaSentiment Flow Through Hyperlink Networks
93 Citations2021Mahalia Miller, Conal Sathi +3 more
This analysis of a large hyperlinked network of mass media and weblog posts to determine how sentiment features of a post affect the sentiment of connected posts and the structure of the network itself indicates that sentiment becomes more polarized as depth increases.
Sentiment Analysis: Extracting Decision-Relevant Knowledge from UGC
76 Citations2013Sergej Schmunk, Wolfram Höpken +2 more
A novel approach for extracting decision-relevant knowledge from UGC is presented and different underlying data mining techniques concerning their accuracy in topic and sentiment detection of textual user reviews are compared.
International Conference on Information TechnologyA Lexicon based sentiment analysis retrieval system for tourism domain.
50 Citations2012Aitor García, Seán Gaines +1 more
The use of lexical databases for Sentiment Analysis of user reviews in Spanish for the accommodation and food and beverage sectors by using the mentioned lexicon database is introduced.
Cambridge University Press eBooksAutologistic Actor Attribute Models
33 Citations2012Galina Daraganova, Garry Robins
This chapter presents a class of cross-sectional network models that, rather than modeling network structure, allows us to understand how individual behavior may be constrained by position in a social network and by behavior of other actors in the network.
RePEc: Research Papers in EconomicsSentiment Analysis: Extracting Decision-Relevant Knowledge from UGC
22 Citations2013Sergej Schmunk, Wolfram Höpken +2 more