<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>2182-8458</journal-id>
<journal-title><![CDATA[Tourism & Management Studies]]></journal-title>
<abbrev-journal-title><![CDATA[TMStudies]]></abbrev-journal-title>
<issn>2182-8458</issn>
<publisher>
<publisher-name><![CDATA[Escola Superior de Gestão, Hotelaria e Turismo da Universidade do Algarve]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S2182-84582014000100010</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Fine-grained analysis of aspects, sentiments and types of attitudes in restaurant reviews]]></article-title>
<article-title xml:lang="pt"><![CDATA[Análise de aspectos, sentimentos e tipos de atitude em avaliações sobre restaurantes]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Chaves]]></surname>
<given-names><![CDATA[Marcirio Silveira]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Laurel]]></surname>
<given-names><![CDATA[André]]></given-names>
</name>
<xref ref-type="aff" rid="A02"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Sacramento]]></surname>
<given-names><![CDATA[Nélia]]></given-names>
</name>
<xref ref-type="aff" rid="A02"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Pedron]]></surname>
<given-names><![CDATA[Cristiane Drebes]]></given-names>
</name>
<xref ref-type="aff" rid="A03"/>
<xref ref-type="aff" rid="A02"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,University Nove de Julho Project Management Program ]]></institution>
<addr-line><![CDATA[São Paulo SP]]></addr-line>
<country>Brazil</country>
</aff>
<aff id="A02">
<institution><![CDATA[,University of Lisbon School of Economics and Management ]]></institution>
<addr-line><![CDATA[Lisbon ]]></addr-line>
<country>Portugal</country>
</aff>
<aff id="A03">
<institution><![CDATA[,University Nove de Julho Business Graduate Program ]]></institution>
<addr-line><![CDATA[São Paulo SP]]></addr-line>
<country>Brazil</country>
</aff>
<pub-date pub-type="pub">
<day>31</day>
<month>01</month>
<year>2014</year>
</pub-date>
<pub-date pub-type="epub">
<day>31</day>
<month>01</month>
<year>2014</year>
</pub-date>
<volume>10</volume>
<numero>1</numero>
<fpage>66</fpage>
<lpage>72</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_arttext&amp;pid=S2182-84582014000100010&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_abstract&amp;pid=S2182-84582014000100010&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_pdf&amp;pid=S2182-84582014000100010&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[This paper presents a novel approach based on the Appraisal Theory to analyze user-generated, open-ended online restaurant reviews. We selected reviews (N=1100) from restaurants of two Portuguese touristic regions and focus, through content analysis, on the recognition of the main aspects, sentiments and types of attitude mentioned in such reviews. We also measure the interrater agreement on the recognition of the types of attitude. The main findings show that Quality of Food, Staff and Communication, Price and Atmosphere are the most frequent aspects mentioned in the reviews. Positive appreciation is the attitude expressed in most of the sentences. Most of the reviews present a positive evaluation of the restaurants. The interrater agreement among raters on the recognition of the types of attitude ranges from 0.82 to 0.92. Results reveal the main aspects that restaurateurs should take into account to make decisions in order to improve the business as a whole.]]></p></abstract>
<abstract abstract-type="short" xml:lang="pt"><p><![CDATA[Este artigo apresenta uma nova abordagem baseada na Teoria de Avaliação para analisar avaliações online abertas e geradas pelo utilizador sobre restaurantes. Foram selecionadas avaliações (n = 1.100) de restaurantes de duas regiões turísticas portuguesas e focamos, através de análise de conteúdo, no reconhecimento dos principais aspectos, sentimentos e tipos de atitude mencionados em tais avaliações. Também foram medidas a concordância entre avaliadores para o reconhecimento dos tipos de atitude. Os principais resultados mostram que a Qualidade da Comida, Pessoal e Comunicação, Preço e Atmosfera são os aspectos mais frequentes mencionadas nas avaliações. Apreciação positiva é a atitude expressa na maioria das frases. A maioria dos comentários apresenta uma avaliação positiva dos restaurantes. A concordância entre avaliadores sobre o reconhecimento dos tipos de atitude varia entre 0,82 e 0,92. Os resultados evidenciam os principais aspectos que os gestores de restaurantes devem considerar para tomar decisões, a fim de melhorar o negócio.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Restaurant management]]></kwd>
<kwd lng="en"><![CDATA[online reviews]]></kwd>
<kwd lng="en"><![CDATA[types of attitude]]></kwd>
<kwd lng="pt"><![CDATA[Gestão de restaurantes]]></kwd>
<kwd lng="pt"><![CDATA[avaliações online]]></kwd>
<kwd lng="pt"><![CDATA[tipos de atitude]]></kwd>
<kwd lng="pt"><![CDATA[teoria de avaliação]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[ <p align="right"><font size="2" face="Verdana"><b>TOURISM - SCIENTIFIC PAPERS</b></font></p>      <p>&nbsp;</p> <font face="Verdana" size="4">     <p><b>Fine-grained analysis of   aspects, sentiments and types of attitudes in restaurant reviews</b></p></font>     <p>&nbsp;</p> <font face="Verdana" size="3">     <p><b>Análise de   aspectos, sentimentos e tipos de atitude em avaliações sobre restaurantes</b></p></font>     <p>&nbsp;</p>     <p>&nbsp;</p> <font face="Verdana" size="2">    <p><b>Marcirio Silveira Chaves<sup>I</sup>; Andr&eacute; Laurel<sup>II</sup>; N&eacute;lia Sacramento<sup>III</sup>; Cristiane Drebes Pedron<sup>IV</sup></b></p>       <p><sup>I</sup>University Nove de     Julho (UNINOVE), Master of Project Management Program, Av. Francisco Matarazzo,     612 - Prédio C - 1º andar, Água Branca - 05001-000 - São Paulo – SP, Brazil, <a href="mailto:mschaves@uninove.br">mschaves@uninove.br</a>    <br>     <sup>II</sup>University of Lisbon, School of Economics and Management (ISEG),   1200-781, Lisbon, Portugal, <a href="mailto:andrelaurel@gmail.com">andrelaurel@gmail.com</a>    ]]></body>
<body><![CDATA[<br>   <sup>III</sup>University of Lisbon, School of Economics and     Management (ISEG), 1200-781, Lisbon, Portugal, <a href="mailto:neliasacramento@gmail.com">neliasacramento@gmail.com</a>    <br>     <sup>IV</sup>University Nove de Julho (UNINOVE), Business Graduate Program,     05001-000, São Paulo – SP, Brazil and University of Lisbon, School of Economics and Management (ISEG), 1200-781, Lisbon, Portugal, <a href="mailto:cdpedron@gmail.com">cdpedron@gmail.com</a></p>     <p>&nbsp;</p>       <p>&nbsp;</p>   <hr noshade size="1">       <p><b>ABSTRACT </b></p>     <p>This paper presents a novel approach based on the     Appraisal Theory to analyze user-generated, open-ended online restaurant     reviews. We selected reviews (N=1100) from restaurants of two Portuguese     touristic regions and focus, through content analysis, on the recognition of     the main aspects, sentiments and types of attitude mentioned in such reviews.     We also measure the interrater agreement on the recognition of the types of     attitude. The main findings show that Quality of Food, Staff and Communication,     Price and Atmosphere are the most frequent aspects mentioned in the reviews.     Positive appreciation is the attitude expressed in most of the sentences. Most     of the reviews present a positive evaluation of the restaurants. The interrater     agreement among raters on the recognition of the types of attitude ranges from     0.82 to 0.92. Results reveal the main aspects that restaurateurs should take     into account to make decisions in order to improve the business as a whole.</p>       <p><b>Keywords:</b> Restaurant management, online reviews, types of attitude, appraisal     theory.</p>   <hr noshade size="1">       <p><b>RESUMO </b></p>     <p>Este     artigo apresenta uma nova abordagem baseada na Teoria de Avaliação para     analisar avaliações <i>online</i> abertas e     geradas pelo utilizador sobre restaurantes. Foram selecionadas avaliações (n =     1.100) de restaurantes de duas regiões turísticas portuguesas e focamos,     através de análise de conteúdo, no reconhecimento dos principais aspectos,     sentimentos e tipos de atitude mencionados em tais avaliações. Também foram     medidas a concordância entre avaliadores para o reconhecimento dos tipos de     atitude. Os principais resultados mostram que a Qualidade da Comida, Pessoal e     Comunicação, Preço e Atmosfera são os aspectos mais frequentes mencionadas nas     avaliações. Apreciação positiva é a atitude expressa na maioria das frases. A     maioria dos comentários apresenta uma avaliação positiva dos restaurantes. A     concordância entre avaliadores sobre o reconhecimento dos tipos de atitude     varia entre 0,82 e 0,92. Os resultados evidenciam os principais aspectos que os     gestores de restaurantes devem considerar para tomar decisões, a fim de     melhorar o negócio.</p>       <p><b>Palavras-chave</b>: Gestão de restaurantes, avaliações <i>online</i>, tipos de atitude, teoria de     avaliação.</p>   <hr noshade size="1">       ]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p>&nbsp;</p></font> <font face="Verdana" size="3">    <p><b>1.   Introduction</b></p></font> <font face="Verdana" size="2">    <p>Web 2.0 sites have allowed consumers to report the pros and cons of     their experiences with companies. Gretzel, Yoo and Purifoy (2007) found that     most people not only read but also write online reviews (83 percent of the     respondents of a survey). Consumers apparently regard user-generated reviews as     more trustworthy than traditional advertising information (Huang, Chou &amp;   Lan, 2007). Consumers also rely on the text of online reviews rather than   average star ratings when evaluating products and services on the Internet   (Godes &amp; Mayzlin, 2004; Schlosser, 2011). </p>     <p>In this context, fine-grained studies on the textual content of online     reviews have gained attention in the tourism industry and, specifically, in the     restaurant industry in the last years (Andaleeb &amp; Caskey, 2007; Namkung   &amp; Jang, 2008; Ha &amp; Jang, 2010; Jo &amp; Oh, 2011; Haghighi, Dorosti,     Rahmana &amp; Hoseinpour, 2012). As reviews are freely available in different     and distributed Web 2.0 information sources, they constitute an important means     of promotion for the restaurant industry. This can be of particular importance     in periods of economic crisis (Pantelidis, 2010). Positive reviews have a     positive impact on the restaurant’s image and on the intentions of purchase by     the customers (Jeong &amp; Jang, 2011). </p>     <p>However, as relevant     as the overall opinion about a restaurant is the specific aspects positively or     negatively mentioned in each review. Pantelidis (2010) refers that a consumer when     visiting a restaurant can like an aspect (e.g. food) but dislike the atmosphere     (or the other way around). When a consumer fails to return, the restaurateur     risks never knowing the reason for that decision. These aspects can also be     observed in the attitude of the customer when describing his/her experience.</p>     <p>While most of the     works focus on the analysis of the main aspects that appear in these reviews,     in this paper we go a step ahead and analyze attitudes expressed in     user-generated, open-ended online reviews. In order to attend this goal we     select online reviews from two touristic regions of Portugal. For this     research, we select the domain of attitude from Appraisal Theory (Martin &amp;   White, 2005). Attitude is concerned with feelings, including emotional   reactions, judgments of behavior and evaluation of things. We are interested in   the perception that consumers have about restaurants and the way these   perceptions are portrayed through online reviews, namely recognizing attitude   types. We also verify the interrater agreement (Cohen, 1960) among human   evaluators in the task of classifying online reviews according to types of   attitudes. </p>     <p>The main objective     of this paper is to recognize the types of attitudes according to the Appraisal     Theory expressed in restaurant online reviews. We also seek to answer the     following research questions: a) What are the most commonly identified attitude     types in restaurant online reviews? b) What is the relation between the     attitudes and the aspects of the restaurants? c) What is the     positivity/negativity expressed in the attitude types in restaurant online     reviews? d) How can online reviews provide useful information to support     restaurateurs' decision-making?</p>     <p>This paper is     structured as follows. We introduce the theoretical background focusing on the     studies of recognition of the main aspects used to describe experiences in     restaurants and in the concepts of the Appraisal Theory. We then describe the     methodology used to collect and analyze the data. In the samples characterization     and the data analysis, we are able to explain the results that were reached.     Following this the interrater agreement is presented. We then discuss the main     theoretical and managerial contributions of this paper. Finally, we conclude by     pointing out limitations and further research.</p>     <p>&nbsp;</p></font> <font face="Verdana" size="3">    ]]></body>
<body><![CDATA[<p><b>2.   Related   Work and Theoretical Background</b></p></font> <font face="Verdana" size="2">    <p><b><i>2.1 Aspects in the     Restaurant Business</i></b></p>     <p>According to Jo and     Oh (2011), the specific aspects mentioned in a review are as important for the     user as the general subject. The same authors define aspect as “...a     multinomial distribution over words that represent a more specific topic in     reviews...” (Jo &amp; Oh, 2011, p.2). Although many authors diverge on the     number of different aspects that should be considered for an analysis of the     restaurant business, three main groups of aspects seem to be taken into account     in most studies (food, service and atmosphere) (Namkung &amp; Jang, 2008). In a     study conducted by Jo and Oh (2011) on restaurant reviews from an online     restaurant guide, the aspects found were mainly related to types of cuisine, or     food, such as “Mexican” or “breakfast” for example, and to other concepts     linked with the restaurant business, like “parking” and “waiting”. Soriano     (2002) considers the existence of four groups of aspects, on his study on     Spain’s restaurant industry, which he considers as determinant factors for a     customer to return to the restaurant. According to his study, “Quality of food”   was the most important aspect, followed by “Quality of service”, “Cost/Value of     the meal” and “Place”.  </p>     <p>According to Kim,     Lee and Yoo (2006), who composed a model to study the relation between the     predictors of relationship quality and the relationship outcomes for luxury     restaurants, there are six main activities that can serve as predictors, or     determinants, in the restaurant business. “Physical environment” and “Food     quality”, which are considered to be tangible, and “Customer orientation”,   “Communication”, “Relationship benefits” and “Price fairness”, the intangible     aspects. The study found that the intangible aspects are the most relevant to     predict relationship quality, rather than the tangible ones. </p>     <p>Haghighi et al.     (2012) studied the factors affecting customer loyalty, through five aspects,   “Food quality”, “Price”, “Service quality”, “Restaurant location” and   “Restaurant atmosphere” (Hyun, 2010). “Food quality” was proven to be the most     important factor, followed by “Restaurant atmosphere”, “Service quality” and   “Price”. For “Restaurant location” the results were not confirmed. Andaleeb and     Caskey (2007), when investigating the factors that influence satisfaction with     food services in a college cafeteria, eight aspects were found: “Cleanliness”,   “Atmosphere”, “Space”, “Convenient hours”, “Food quality”, “Staff behaviour”,   “Price” and “Responsiveness”. The study showed that the “Food quality” and   “Price” were the ones that triggered more dissatisfaction and, therefore,     caused the most impact on the studied population. </p>     <p>Pantelidis (2010) studied online reviews on full-service restaurants in     the London area, on an online restaurant guide. The author found that the six     most repeated factors, or aspects, mentioned in the comments analyzed were   “Food”, “Service”, “Atmosphere”, “Price”, “Menu” and “Design”. As in other     studies above mentioned, “Food” was the most talked-about aspect in the study.     Therefore, it is the main aspect that customers refer to, when recalling the     experience being commented. “Service” and “Atmosphere” were the second and     third most mentioned aspects, after “Food”. This evidence is in accordance with     other studies mentioned. <a href="/img/revistas/tms/v10n1/10n1a10t1.jpg">Table 1</a> presents the full list of aspects used in our     work based on literature review.</p>     
<p><b>2.2     Appraisal Theory</b></p>     <p>Appraisal     belongs to a group of three main discourse semantic resources that interpret     interpersonal meaning, the others being “involvement” and “negotiation” (Martin &amp; White, 2005).     Appraisal is then divided into three categories, “attitude”, “engagement” and   “graduation”. This work will focus only on “attitude” and its three domains,   “affect”, “judgement” and “appreciation”.</p>     <p>Martin and White     (2005) connects “attitude” to feelings, which, for the authors, include     emotional reactions and the evaluation of certain behaviors and things. For     example, feeling happy with a certain meal experience or the act of judging the     behavior of employees can be considered as attitudes, in this case, affect and     judgement, respectively.</p>     <p>“Affect” is     something that causes someone to have feelings, of sympathy or sadness, towards     somebody or something. Therefore it is connected with emotional reactions     (Martin &amp; White, 2005). It also reflects an emotional state (Chaves &amp; Picoto, 2012). One     example of this kind of “attitude”, taken from a review analyzed in the present     work, is the sentence “Loved the atmosphere...”. It clearly shows a feeling of     affect that the reviewer has towards something. In this case, the reviewer     demonstrates “love” about the aspect “atmosphere”.</p>     ]]></body>
<body><![CDATA[<p>“Judgement” is an     opinion about something or, as Chaves and Picoto (2012) state, about the     behavior of others. An example of “Judgement” can be illustrated by the     following sentence, concerning a restaurant commentary: “The staff really cares     about you”. In this sentence, the reviewer is explicitly giving his opinion     about the behavior of the staff. Thereby judging the aspect mentioned.</p>     <p>“Appreciation” can     be characterized as enjoyment and understanding of something. It is then     concerned with the intrinsic value that one attributes to something (Martin &amp; White, 2005; Chaves &amp; Picoto, 2012). The sentence “The food was totally delicious and worth     every single penny.” is an example of “appreciation” about the food.</p>     <p>&nbsp;</p></font> <font face="Verdana" size="3">    <p><b>3.   Methodology</b></p></font> <font face="Verdana" size="2">    <p>This work makes a     thorough analysis of 1100 online reviews on restaurants in Lisbon (Lisbon and     surroundings) and Algarve (touristic region in the South of Portugal). The     reviews were taken from tripadvisor.com, which was selected because of its     world-wide usage, being available in 30 countries and with over 100 million     reviews and opinions (TripAdvisor.com, 2013). For the analysis, the following     steps were taken.</p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; First Stage: Selection of the top ranked     restaurants in the summer period in both regions, from 21st of June to 21st of     September, 2012. The analyzed ranking, on tripadvisor.com, was the one     registered on the last day of the studied period, on 21st of September.</p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Second Stage: From the restaurants selected,     we collected reviews in accordance with the following criteria:</p>     <p>o&nbsp;&nbsp; We selected a maximum of 30 reviews per     restaurant. For the restaurants that exceeded this number during the period     studied, only the first 30 reviews in inverse chronological order, were     considered. </p>     <p>o&nbsp;&nbsp; Each review needed to have a minimum of 50     characters, without considering spaces. This procedure helps to avoid spams in     the collection phase. </p>     <p>o&nbsp;&nbsp; All the reviews were searched and selected     from the most recent to the least recent.</p>     ]]></body>
<body><![CDATA[<p>o&nbsp;&nbsp; We considered the reviews written in     Portuguese, Spanish, English and French.</p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Third Stage: We applied Content Analysis     (Bardin, 2009) in order to analyze sentences. After being transposed to a     spreadsheet, we divided the reviews into sentences and analyzed, manually and     individually, each segment of the sentences. A segment is a sequence of words     mentioning any of these items: </p>     <p>o&nbsp;&nbsp; “Aspect”: sentences contain aspects that     constitute the object that is being reviewed. These aspects consist of specific     concepts of the restaurant business. For this study, we used the eleven aspects     described in <a href="/img/revistas/tms/v10n1/10n1a10t1.jpg">Table 1</a>. </p>     
<p>o&nbsp;&nbsp; “Sentiment”: the general sentiment of a given     sentence was classified into four categories (positive, negative, neutral or     not applicable (N/A)).</p>     <p>o&nbsp;&nbsp; “Attitude”: by applying the Appraisal Theory,     we analyze the attitude expressed in each sentence (if it exists) in its three     dimensions - affect, judgement and appreciation as described in the previous     section.</p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Fourth     Stage: After all the sentences were classified, the objective of this stage is     to understand the relation between the different items in the sentence to help     the decision-making process of restaurateurs and customers or prospects.</p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Fifth Stage: The last stage consists on the     evaluation of the interrater agreement. We randomly select 20 percent of each     sample and ask two more subjects to classify the sentences according to the     attitude types.</p>     <p><b>3.1     Samples Characterization</b></p>     <p>This paper describes     a research using two samples of online reviews from two touristic regions of     Portugal. <a href="#t2">Table 2</a> shows a summary of the data collected and analyzed. The total     value of distinct sentences is the sum of each distinct sentence into each     review. A segment is a sequence of words in a sentence. One sentence can     contain more than one segment. </p>     <p><a name="t2"></a></p>     ]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p align="center"><img src="/img/revistas/tms/v10n1/10n1a10t2.jpg" width="381" height="201"></p>     
<p>&nbsp;</p>     <p>Descriptive   statistics of the samples gives a better overview of the content to be mined to   support decision making. Lisbon reviews have, on average, almost 5 sentences   per review, while reviews from Algarve contain 5,5 sentences per review. For   both samples, 60 percent of the sentences contain at least one aspect mentioned   and around one-fifth of the sentences contain more than one aspect.  </p>     <p><a href="#t3">Table 3</a> presents the     distribution of the Types of Reviewers according to the TripAdvisor     categorization. As around 30 percent of the reviewers do not indicate a type,     any inference about this data can be biased. </p>     <p><a name="t3"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/tms/v10n1/10n1a10t3.jpg" width="383" height="191"></p>     
<p>&nbsp;</p>     <p>We     also try to use the type of cuisine of each restaurant, 29 percent of the     sample from Algarve is Portuguese and the remaining types were distributed in     minority (6% or less) representation. However, almost 40 percent of the     restaurants analyzed do not provide this information in the case of the     Algarve. In face of this data, any interpretation tends to be inconclusive.</p>     ]]></body>
<body><![CDATA[<p>In regard to the     aspects assigned to the sentences, <a href="#f1">Figure 1</a> shows that the more frequent     aspects are Quality of food, Staff and Communication, Price, Atmosphere,     Quality of Service and Variety of Menu in     the reviews of both samples.</p>     <p><a name="f1"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/tms/v10n1/10n1a10f1.jpg" width="367" height="264"></p>     
<p>&nbsp;</p>     <p>&nbsp;</p></font> <font face="Verdana" size="3">    <p><b>4.   Data Analysis</b></p></font> <font face="Verdana" size="2">    <p>This section     presents an analysis of all parameters classified for both samples of online     reviews. We perform this task searching to     identify tendencies among the parameters. Firstly, we analyze the sentiment -     positive or negative - assigned to each aspect. We then identify the type of     attitude assigned to each aspect and the relation among types of attitude,     aspects and sentiments. At the end, we describe the interrater agreement     analysis regarding to the three types of attitudes in each sample. Percentage     results presented henceforward are about the total number of segments of each     sample according to <a href="#t2">Table 2</a>.</p>     <p><b>4.1     Sentiments Assigned to Aspects and to Types of Attitude</b></p>     <p>As relevant as     knowing the more frequent aspects mentioned in online restaurant reviews is to     analyze the sentiment associated to each aspect. <a href="/img/revistas/tms/v10n1/10n1a10t4.jpg">Table 4</a> presents the results     grouped by geographic region. According to these results, more than 60 percent     of the segments mention at least one aspect of the restaurants in both samples.     Although the positive sentiment predominates, it is worth mentioning that     Service Responsiveness received a considerable number of negative evaluations.     Convenient Hours and Cleanliness rarely are mentioned in the reviews of both     samples. </p>     
]]></body>
<body><![CDATA[<p>We     are also interested in analyzing the sentiments assigned to types of attitudes     in online restaurant reviews. It is relevant to highlight that more than 65     percent of the segments evaluated in each sample contain at least one type of     attitude expressed by customers. First, we verify the overall sentiment     associated to each type of attitude. According to <a href="/img/revistas/tms/v10n1/10n1a10t5.jpg">Table 5</a>, positive     appreciation is the uppermost sentiment and attitude in both samples. Although     affect has been the less frequent type of attitude, when expressed, it is in a     positive way. On the other hand, there was no positive judgement in the Algarve     reviews. </p>     
<p><b>4.2     Fine-grained Analysis of the Main Aspects Mentioned in Online Restaurant     Reviews</b></p>     <p>This section allows     restaurateurs to see the “big picture” of the attitudes assigned to the aspects     and the sentiments associated to each type of attitude. <a href="/img/revistas/tms/v10n1/10n1a10t6.jpg">Table 6</a> shows that for     most of the aspects, positive appreciation is the most frequent type of     attitude, except for the aspect of Staff and Communication where the positive     judgement is the most referred one in Lisbon reviews. </p>     
<p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <b>Quality of food</b>: Positive     appreciation was the sentiment and attitude more representative for this aspect     in both regions reviewed.</p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <b>Staff and     Communication</b>: For Lisbon reviews, positive judgement was the     sentiment and attitude more representative for this aspect. On the other hand,     for the Algarve reviews, positive appreciation was the most frequent. Taking     into account that affect rarely appears in online restaurant reviews, it is interesting     to note that Staff and Communication received more than 20 percent of the     sentences positively evaluated about this aspect in the Algarve region reviews.</p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <b>Price</b>: This aspect is     also evaluated as positive appreciations in both samples. There was no sentence     classified as affect to this aspect. </p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <b>Atmosphere and     Variety of Menu</b>: These aspects received more than 80 percent of     positive appreciations in both samples. Judgements and affects rarely appeared.</p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <b>Quality of Service</b>: Although positive     appreciation is also the uppermost sentiment and attitude assigned to this     aspect, it is worth noting that judgements were expressed in a negative way in     the reviews of the Algarve region.</p>     <p><b>4.3     Ratings</b></p>     <p>We also verify if     the rating given by customers correspond to the sentiment assigned by the human     evaluator. This analysis tries to find the relation between the quantitative     evaluation of the customer (rating which ranges from 1 to 5) and the     qualitative evaluation assigned by the human evaluator (the polarity of the sentiment). </p>     ]]></body>
<body><![CDATA[<p>Overall,     the 5-star scale rating system is in accordance with the sentiment of the     sentences. For reviews classified with 1-star, the majority of sentences are     negative. For 5-star reviews, most of the sentences refer to a positive     experience. However, we observe a reverse polarity in both samples. For reviews     classified as 4- and 5-star, human evaluators found 75 and 99 negative     sentences in Lisbon and Algarve reviews, respectively. On the other hand, for     reviews classified as 1- and 2-star, human evaluators found 9 and 24 positive     sentences in Lisbon and Algarve reviews, respectively.</p>     <p>These results     indicate that ratings do not always reflect the full meaning of the review.     Therefore analyzing reviews at the sentence level can provide a more accurate     understanding of the reviewer’s experience.</p>     <p><b>4.4     Interrater Agreement</b></p>     <p>Considering the     subjectivity of the classification task, we did a random selection of each     sample (reviews from the Lisbon region and Algarve) and asked two more raters     to classify each sentence according to the three types of attitude previously     described. For both samples, we perform an analysis of the interrater agreement     on a random selection of 20 percent (891 sentences) of the sentences with some     attitude assigned by the evaluators. </p>     <p>Considering that little guessing is likely to     exist, we rely on the percent agreement to determine interrater reliability.     <a href="#t7">Tables 7</a>, <a href="#t8">8</a> and <a href="#t9">9</a> present the confusion matrix for each pair of raters, who     evaluate restaurant reviews in the Lisbon region. Agreements between the two     raters are placed in one of the diagonal cells. <a href="#t7">Table     7</a> shows that rater A has placed 291 classifications as appreciation, rater B     has placed 237 for appreciation, 27 for judgement and 27 for affect.     Considering all values in <a href="#t7">Table 7</a>, the interrater agreement between rater A and     B was 82%, which is reached through the sum of the agreements in the diagonal     (275) by the total number of classifications (337). The interrater agreement     between rater A and C was 84% and between rater B and C was 83%. We also     calculate the interrater agreement between raters of     reviews of the Algarve. Raters A and B reached an agreement of 92%, between     raters A and C it was 90% and between rater B and C it was 83%. <a href="#t10">Tables     10</a>, <a href="#t11">11</a> and <a href="#t12">12</a> show the confusion matrix for each pair of raters who evaluate     restaurant reviews in the Algarve.</p>     <p><a name="t7"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/tms/v10n1/10n1a10t7.jpg" width="351" height="165"></p>     
<p>&nbsp;</p>     <p><a name="t8"></a></p>     ]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p align="center"><img src="/img/revistas/tms/v10n1/10n1a10t8.jpg" width="354" height="180"></p>     
<p>&nbsp;</p>     <p><a name="t9"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/tms/v10n1/10n1a10t9.jpg" width="356" height="183"></p>     
<p>&nbsp;</p>     <p><a name="t10"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/tms/v10n1/10n1a10t10.jpg" width="360" height="147"></p>     
]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p><a name="t11"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/tms/v10n1/10n1a10t11.jpg" width="363" height="155"></p>     
<p>&nbsp;</p>     <p><a name="t12"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/tms/v10n1/10n1a10t12.jpg" width="363" height="157"></p>     
<p>&nbsp;</p>     <p>&nbsp;</p></font> <font face="Verdana" size="3">     ]]></body>
<body><![CDATA[<p><b>5.   Discussion </b></p></font> <font face="Verdana" size="2">    <p><b>5.1 Theoretical     implications</b></p>     <p>In     our study around 50 percent of the reviews talk about three aspects: Quality of     Food, Staff and Communication and Price. This fact is in line with the results     found by Andaleeb and Caskey (2007), that obtained the same top 3 aspects,     although with different results for polarity. Contrary to the findings of     Andaleeb and Caskey (2007), where the aspects in relation to quality of food     and price were the ones that triggered more dissatisfaction, in our study most     of the references to these aspects were positively evaluated. Pantelidis (2010)     has also found that favorable reviews far outnumbered negative comments.</p>     <p>Quality of Food is     usually the most mentioned and most important attribute in the literature     (Pantelidis, 2010; Soriano, 2002; Andaleeb &amp; Caskey, 2007; Haghighi et al.,     2012). Staff and Communication, and Price are also top mentioned attributes in     studies by Kim et al. (2006), Andaleeb and Caskey (2007), Pantelidis (2010) and     Soriano (2002). Atmosphere is also usually widely cited (Namkung &amp; Jang,     2008; Ha &amp; Jang, 2010; Kim et al., 2006; Haghighi et al., 2012; Pantelidis,     2010). Ha and Jang (2010) refer that atmosphere has an important effect in     customer behavior and it can also influence the customer’s desires in     experiencing other aspects. However, it was only the fourth most mentioned in     our study. </p>     <p>We also highlight     the relevance of reviews with reverse polarity in both samples. Positive     ratings contain negative sentences and negative reviews contain positive     sentences. As noted by Pantelidis (2010), when a consumer fails to return, the     restaurateur risks never knowing the reason.</p>     <p>The percentage     distribution of the attitude types for online restaurant reviews found in this     work is inline with the results described in Taboada and Grieve (2004) for the     domains books, computer, hotels, music, phones, movies, cars and cookware. In     their study, appreciation is the attitude present in at least 50 percent of the     reviews in all of these domains, followed by judgement and affect.</p>     <p>It is also relevant     to stress the importance of the positive online reviews. These contents should     be better used by restaurateurs. Floh, Koller, &amp; Zauner (2013) researching     online reviews for hotels, books, and running shoes, found that the valence intensity of online reviews     moderates the effect of online reviews on purchase intentions. They found a     significant change in online shopping behavior for positive medium and strong     reviews but not for negative ones. </p>     <p>Concerning the agreement between raters, the average Kappa was above     0,5 in both samples. Although it is considered as “Moderate Agreement”   (LeBreton &amp; Senter, 2008), this value can be interpreted as satisfactory     given the subjectivity of analyzing Attitude at sentence segment level.</p>     <p><b>5.2     Managerial Implications for Restaurateurs</b></p>     <p>As a result of this     research, we discovered a set of relevant findings that can be used by     restaurateurs in order to improve their decision making.</p>     ]]></body>
<body><![CDATA[<p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Quality of food, Staff and Communication, Variety of Menu, and Price are     the more frequent aspects with positive sentiment.     This finding evidences that the restaurants in both samples analyzed provide a     product (food) and service with satisfactory quality. This fact should motivate     restaurateurs to encourage customers to write reviews, which can influence the     prospects' decision making. Melián-González, Bulchand-Gidumal   &amp; López-Valcárcel (2013), working on reviews     about hotels, found that as participation increases, better evaluation is     obtained. Moreover, abilities such as sympathy, good communication and     understanding of customer’s needs are also greatly appreciated by reviewers.     Restaurateurs should pay more attention to this item by giving continuous     motivation and training to their staff, so they can improve their communication     and cognitive skills. Price, also having mostly positive reviews, shows that     people recognize when they pay a fair price for their meal.</p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Reviews about     Service Responsiveness tend to be negative: Although most of the aspects have     been positively evaluated, Service Responsiveness     received more negative than positive reviews     in the Lisbon region and as many positive as negative in the Algarve region.     Restaurateurs should pay more attention to this aspect and try to find out the     reasons that lead to this dissatisfaction by customers. </p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Positive     appreciation is the central attitude type in online     restaurant reviews: In regard to types of attitudes,     positive appreciation was the most frequent in both samples. This finding     evidences a positive overall evaluation of the restaurants in both regions of     Portugal. For this reason, managers should not be     afraid of their business going on websites such as Tripadvisor.com.</p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; For Algarve reviews, judgements about Staff and Communication, when made, tended to be negative: We noted that     judgements made about Staff and Communication in restaurants in the Algarve     region were in a negative way, contrary to the judgements about this aspect in     the Lisbon region, where they rarely appear. This fact indicates that the     behavior of the Staff should be improved in the restaurants in the Algarve     region.  </p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Affective expressions rarely appear in online restaurant reviews: This fact occurs     in both samples evidencing that customers are more interested in evaluating the     product and the service than making emotional testimonials.  </p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; High ratings also contain negative references about specific aspects of     restaurants: Although most aspects have been     evaluated with positive sentiment, more than one hundred and fifty sentences     contain at least one negative mention to one aspect of the restaurant in both     samples. This fact highlights the relevance of a fine-grained analysis at a     segment sentence level in order to mine     this kind of knowledge. </p>     <p>·&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; Betting     on quality of food even in a context of economic recession. In both samples, the aspect of price was mentioned around three times     less than quality of food. Taking into account that the time frame of the     analyzed reviews correspond to a period of financial crisis in Portugal and     Europe, results indicate tha<b>t </b>restaurateurs can remain betting on     quality of food rather than cutting prices. </p>     <p>&nbsp;</p></font> <font face="Verdana" size="3">    <p><b>6.   Conclusions</b></p></font> <font face="Verdana" size="2">    <p>The fine-grained     analysis of the opinion of customers about restaurants presented in this paper     can help restaurateurs to better decision making in an economic crisis period.     Moreover, marketing managers can also be direct beneficiaries of the results     described in this research. We used samples from two well-known regions of     Portugal, which ensures that our findings are practical and influential. </p>     ]]></body>
<body><![CDATA[<p>Another     contribution of this work is to provide a freely available resource composed of 891 annotated sentences to evaluate systems     dealing with sentiment analysis. The list of sentences and the evaluation of     the six raters is available at (self reference).</p>     <p>Further     research includes the application of the same methodology to a wider sample of     restaurants analyzing aspects by type of cuisine, profile of consumer and size     of restaurant. In addition, we can evaluate other domains such as reviews about     hotels and trips as the types of attitudes of the consumers.</p>     <p>Finally, to the best     of our knowledge, this is the first study on recognizing types of attitudes     expressed in restaurants online reviews, as well as on the evaluation of the     interrater agreement in this domain. Whereas over than 65 percent of the     sentences evaluated in each sample contains at least one type of attitude     expressed by customers, it is worth looking into other online restaurant     collections to observe if this phenomenon repeats itself.</p>     <p>&nbsp;</p></font> <font face="Verdana" size="3">    <p><b>References</b></p></font> <font face="Verdana" size="2">    <!-- ref --><p>Andaleeb, S. &amp; Caskey. A. (2007). Satisfaction with food services:     Insights from a college cafeteria. <i>Journal     of Foodservice Business Research</i>, <i>10</i>(2),     51-65.    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000148&pid=S2182-8458201400010001000001&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --></p>     <!-- ref --><p>Bardin, L. (2009). <i>Análise de Conteúdo</i>. Lisboa: Edições 70.    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000150&pid=S2182-8458201400010001000002&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --></p>     <p>Chaves, M. S. &amp;   Picoto, W. (2012). A Multidomain and Multilingual Conceptual   Data Model for Online Reviews Representation.&nbsp;<i>Proceedings of the 7th International Conference on Software Paradigm     Trends</i> (ICSOFT 2012), Roma, Italy, 24-27 July, 14-23.</p>     ]]></body>
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Customers’ expectations factors in restaurants: The     situation in Spain. <i>International Journal     of Quality &amp; Reliability Management</i>, <i>19</i>(8), 1055-1067.    &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=000186&pid=S2182-8458201400010001000021&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --></p>     <p>Taboada, M. &amp; Grieve, J. (2004). Analyzing     appraisal automatically. In Proceedings of <i>AAAI     Spring Symposium on Exploring Attitude and Affect in Text</i> (AAAI Technical     04/07), Stanford University, CA, 158-161. AAAI Press.</p>     <p>&nbsp;</p>     <p>&nbsp;</p>     <p><b>Acknowledges </b></p>     <p>We gratefully acknowledge financial     support from FCT- Funda&ccedil;&atilde;o para a Ci&ecirc;ncia e Tecnologia (Portugal), national     funding through research grant (PEst-OE/EGE/UI4027/2011).</p>     ]]></body>
<body><![CDATA[<p>&nbsp; </p> </font><font face="Verdana" size="2">    <p><b>Article     history:</b></p>         <p>Submitted: 30 June 2013</p>         <p>Accepted: 10 November     2013</p> </font>      ]]></body><back>
<ref-list>
<ref id="B1">
<nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Andaleeb]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Caskey]]></surname>
<given-names><![CDATA[A.]]></given-names>
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