17 research outputs found

    Weakly-supervised appraisal analysis

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    This article is concerned with the computational treatment of Appraisal, a Systemic Functional Linguistic theory of the types of language employed to communicate opinion in English. The theory considers aspects such as Attitude (how writers communicate their point of view), Engagement (how writers align themselves with respect to the opinions of others) and Graduation (how writers amplify or diminish their attitudes and engagements). To analyse text according to the theory we employ a weakly-supervised approach to text classification, which involves comparing the similarity of words with prototypical examples of classes. We evaluate the method's performance using a collection of book reviews annotated according to the Appraisal theory

    APPRAISING TWITTER USERS’ ATTITUDE ON “WRITING LAST LINE STORY”: SFL APPROACH ON CLOSING STATEMENT IN CYBER LITERATURE

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    Twitter, an online platform that is said to have a more constructive and meaningful response to the issues, is also where people are creative writers of cyber literature. Lately, there has been a trend of Twitter users to write fiction lines that have a premise of “what is your last line if you in the ending of a relationship.” This research intended to seek the attitude of Indonesian writing fiction in English. This paper analyses a short written online discourse called ‘tweet’ using Systemic Functional Linguistics (SFL). This analysis focuses on appraising attitudes that are feeling on reacting to emotion, putting the judgment, and evaluating things. The data is taken from a Twitter account, namely @literarybase, by shorting 100 popular tweets taken to seek the trend and 20 tweets among them to be classified on its appraisal criterion. The results show that a relationship's trend ends with a sad ending rather than a happy ending. However, positive affection holds the most significant shares of lexical choice, followed by judgment and appreciation the least. That means the users mostly used ironic writing that contrasts expectation with reality. Linguistic research also implied that tragedy plot is favorable in online discourse. The study has identified the practical way of assessing attitudes in short-writing fiction on online platforms and the tendency of a community to see value in a relationship and how they express themselves in a foreign language.

    An Empirical Study of Social Media Exchanges about a Controversial Topic: Confirmation Bias and Participant Characteristics

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    There has been a significant amount of research into social media commentary influences on human behaviors, ranging from its role in affecting political elections to predicting corporate revenues; however, to this point, the factors and influences of social media have not been completely explained and it is not entirely clear whether social media influences or simply confirms preconceptions. Moreover, with sentiment analysis, much of the research has relied on human expert interpretation of the sentiments and semantics written in various social media. It has also tended to be interpretive rather than predictive in nature. In our study, we wanted to know if social media conversations were reflective or influencers of human behavior. Using a social media mining technology we were able to determine sentiments, sentiment intensity, and the characteristics of participants. We found strong evidence of confirmation bias, but that bias was influenced by personal characteristics, and in some cases, whether the sentiments were strongly positive or strongly negative

    An Ontology Artifact for Information Systems Sentiment Analysis

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    As companies and organizations increasingly rely on on-line, user-supplied data to obtain valuable insights into their operations, sentiment analysis of textual data has proven to be a most valuable resource. To understand how sentiment analysis can be used effectively, it is important to identify what types of sentiment analysis could be employed during the analysis of a given situation. This research proposes an Information Systems Sentiment Ontology, the purpose of which is to provide a basis for mining and understanding sentiment, specifically from text provided by customers as online content. The Information Systems Sentiment Ontology is developed by analyzing the literature on emotion, sentiment analysis, and ontology development and from prior research on online forum analysis. A traditional design science approach is followed to the ontology development. Details on the creation and application of the ontology artifact are provided

    Az ismeretlen ismerős. A neuromarketing iránti attitűdök szentimentelemzése

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    A neuromarketing a 2010-es évek második felére elfoglalta az őt megillető helyet mint akadémiai kutatási terület és mint gyakorlati piackutatási tevékenység egyaránt. Világszerte alkalmazzák jobbára termékfejlesztési célokra, illetve a fogyasztói motivációk és döntéshozatali metódusok pontosabb definiálására. Mégis, a szakirodalomból hiányzik a neuromarketing mint jelenség iránti fogyasztói attitűdök feltárása: a kezdeti etikai problémák és szakmai balfogások nagyban hátráltatták reputációjának építését, így jellemzően negatív konnotáció övezi a közvélemény részéről. Vizsgálatuk során a szerzők ezt a hiányt igyekeznek pótolni: a SentiOne social listening szoftver segítségével összegyűjtötték a közösségi médiában 2017-ben és 2018-ban megjelent összes „neuromarketing” említést, majd tartalomelemzés segítségével csoportosították őket. Eredményeikben feltárják a neuromarketinggel kapcsolatos megnyilvánulások általános helyzetét, kategorizálják a nyilvános tartalmakat, ezáltal felvázolnak egy szofisztikáltabb képet a neuromarketing iránti attitűdökről. Megvizsgálva, hogy ezek hogyan viszonyulnak a tudományterület elméleti felvezetésükben részletezett valós helyzetéhez, eredményeik segítségével fényt próbálnak deríteni arra, hogy a tudományos diskurzuson és kutatásokon, valamint a piaci-gyakorlati alkalmazásokon túl milyen általános nevelő feladat hárul a terület művelői számára a terület elfogadásának növelésére

    The brand equity of a destination: A user-generated content analysis

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    Customer-based brand equity can be defined as the differential effect of brand knowledge on consumer response to the marketing of the brand. Although there are already studies focused on the brand equity of destinations, most of them are based on surveys. Still, it is possible to extract and analyse visitors’ opinion by their self-reported experience that is available on travel blogs, in which bloggers write in a way that best represents their experience. Tourism in Lisbon has been increasing over the last years and Portugal is one of the most visited countries in Europe. The novelty of this dissertation is to propose a new methodology of measuring brand equity through text-mining of user-generated blog posts, based on the visitors’ evaluations of Lisbon. For this purpose, 100 posts were collected to test a brand equity model measured by four constructs: brand awareness, brand image - decomposed in cognitive, affective, and unique image components, perceived quality, and brand loyalty. Findings revealed that the components of destination image are highly related, with the cognitive image being strongly related to higher destination brand image. Regarding to the constructs, awareness and image are the most important to make the consumers loyal to Lisbon, with image and perceived quality representing the strongest relationship between constructs. Further, higher awareness can lead to negative perceived quality, but the image can work as a moderator of this relationship. Perceived quality was the only construct that did not reveal a significant relationship with destination loyalty.O valor da marca baseado no cliente pode ser definido como o efeito diferencial do conhecimento da marca na resposta do consumidor ao marketing da marca. Embora existam estudos focados no valor da marca dos destinos, a maioria são baseados em questionários. Contudo, é possível extrair e analisar a opinião dos visitantes através do seu relato da experiência, disponível em blogs de viagens, nos quais os bloggers escrevem da forma que melhor representa a sua experiência. O turismo em Lisboa tem aumentado nos últimos anos e Portugal é um dos países mais visitados da Europa. A novidade desta dissertação é propor uma nova metodologia para medir o valor da marca através da mineração de dados de publicações em blogs, baseada na avaliação dos visitantes de Lisboa. Para isso, 100 publicações foram recolhidas para testar um modelo de valor da marca medido por quatro construtos: notoriedade, imagem - decomposta em componentes cognitivos, afetivos e imagem única, qualidade percebida e lealdade. Os resultados revelaram que as componentes da imagem do destino estão altamente relacionadas, com a imagem cognitiva fortemente relacionada à imagem da marca. Relativamente aos construtos, a notoriedade e a imagem são os mais importantes para fidelizar os consumidores a Lisboa, com a imagem e a qualidade percebida representando a relação mais forte entre eles. Além disso, maior notoriedade pode levar a qualidade percebida negativa, mas a imagem pode funcionar como moderadora desta relação. A qualidade percebida foi o único construto que não revelou relação significativa com a lealdade ao destino

    A Machine Learning Approach for Plagiarism Detection

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    Plagiarism detection is gaining increasing importance due to requirements for integrity in education. The existing research has investigated the problem of plagrarim detection with a varying degree of success. The literature revealed that there are two main methods for detecting plagiarism, namely extrinsic and intrinsic. This thesis has developed two novel approaches to address both of these methods. Firstly a novel extrinsic method for detecting plagiarism is proposed. The method is based on four well-known techniques namely Bag of Words (BOW), Latent Semantic Analysis (LSA), Stylometry and Support Vector Machines (SVM). The LSA application was fine-tuned to take in the stylometric features (most common words) in order to characterise the document authorship as described in chapter 4. The results revealed that LSA based stylometry has outperformed the traditional LSA application. Support vector machine based algorithms were used to perform the classification procedure in order to predict which author has written a particular book being tested. The proposed method has successfully addressed the limitations of semantic characteristics and identified the document source by assigning the book being tested to the right author in most cases. Secondly, the intrinsic detection method has relied on the use of the statistical properties of the most common words. LSA was applied in this method to a group of most common words (MCWs) to extract their usage patterns based on the transitivity property of LSA. The feature sets of the intrinsic model were based on the frequency of the most common words, their relative frequencies in series, and the deviation of these frequencies across all books for a particular author. The Intrinsic method aims to generate a model of author “style” by revealing a set of certain features of authorship. The model’s generation procedure focuses on just one author as an attempt to summarise aspects of an author’s style in a definitive and clear-cut manner. The thesis has also proposed a novel experimental methodology for testing the performance of both extrinsic and intrinsic methods for plagiarism detection. This methodology relies upon the CEN (Corpus of English Novels) training dataset, but divides that dataset up into training and test datasets in a novel manner. Both approaches have been evaluated using the well-known leave-one-out-cross-validation method. Results indicated that by integrating deep analysis (LSA) and Stylometric analysis, hidden changes can be identified whether or not a reference collection exists

    アプレイザル理論を基底とした評価表現の分類と辞書の構築

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    情報通信研究機構ユニバーサルコミュニケーション研究所Universal Communication Research Institute, National Institute of Information and Communications Technology本研究は,大規模データから抽出された評価情報の集約方法として評価極性だけでなく価値基準の種類による集約が可能となるように,価値基準の種類を観点として日本語の評価表現の分類体系を記述し,さらに,価値基準の種類と評価表現の対応関係を記述した言語資源を構築することを目的とする。また,記述した分類体系の妥当性について大規模コーパスを用いて検討する。一般的な国語辞典より評価表現8,544件を収集し,これら全てを価値基準の種類を観点として分類できる体系を,アプレイザル理論における英語のattitudeの枠組みを再構築することで記述した。さらに,記述した体系を用いて価値基準の種類の分類情報を付与した評価表現辞書を作成した。この辞書を用いて『現代日本語書き言葉均衡コーパス』の書籍データで使用されている評価表現182,351件を特定し,評価表現が示す価値基準の種類と日本十進分類法のカテゴリの対応関係についてコレスポンデンス分析を用いて調べた。分析の結果,分類体系において共通の上位カテゴリをもつ評価表現は共通の上位カテゴリをもたない評価表現に比べて,類似した文脈で使用されていることが明らかになった。Harrisの分布仮説では,類似した文脈に出現するものは,意味的にも類似した性質をもつとされていることから,分析結果は,大規模コーパスにおける評価表現の使用傾向から,記述した分類体系の妥当性を支持するものであると考えられる。This study aims to describe the classification of Japanese evaluative expressions according to value types, and to construct a dictionary of attitudinal lexis based on the classification. For the classification, the English system of ATTITUDE proposed by Appraisal theory was modified for application to Japanese based on the examination of 8,544 evaluative expressions that were collected from a dictionary. As for the construction of the dictionary of attitudinal lexis, the 8,544 expressions were annotated based on the modified system of ATTITUDE. In addition, the present study tested the validity of the modified system, using the Balanced Corpus of Contemporary Written Japanese. From the corpus, 182,351 evaluative expressions were identified, and the relationship between the types of evaluative expressions and the categories of the Nihon Decimal Classification were investigated using a multivariate statistical analysis. The result of the analysis indicates that similar categories in the modified system are, in fact, utilised in the same or similar kinds of Nihon Decimal Classification categories, supporting the validity of the modified system from the perspective of Harris\u27s distributional hypothesis

    Social intelligence: para além do social media listening: o caso EDP

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    Relatório de estágio apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.A chamada web 2.0 e o surgimento das redes sociais trouxeram consigo novas formas de comunicar que introduziram um novo paradigma comunicacional, revolucionando o modo como as empresas se relacionam com os consumidores. Estes novos desafios com que o marketing se depara conduziram à necessidade de incluir estes influentes mas também potencialmente arriscados instrumentos à disposição da empresa, aproveitando o grande volume de informação que está à disposição nas redes. Contudo, há questões de privacidade que se devem ter em consideração. Para que seja possível a criação de uma relação forte com os consumidores, é necessário, primeiro, estudar o que se diz nas redes sociais, o social media listening. De facto, é fulcral saber o que se diz de forma a criar estratégias de marketing que permitam a construção de relações fortes e duradouras existindo, para o efeito, ferramentas apropriadas, nas quais se baseia o social media listening. Foi neste contexto que surgiu o estágio realizado na EDP. Respeitando o método de investigação-acção, este estágio tinha por objectivo analisar o conteúdo das conversas relativas à empresa nas redes sociais, de modo a serem retirados insights relevantes para a EDP. O trabalho desenvolvido ao longo do estágio resultou num relatório mensal, tendo em conta métricas específicas do meio digital, baseando-se, sobretudo, na contagem de menções e análise de sentimento. A actualidade do tema e a escassa literatura científica acerca do mesmo justificam a importância deste estudo no âmbito do qual se apresenta um modelo de relatório que visa auxiliar as empresas a desenvolver estratégias com base nestes novos dados, particularmente na área do marketing.ABSTRACT : The so-called web 2.0 and the emergence of the social networks brought along new forms of communication that introduced a new communicational paradigm and changed the way enterprises related to their consumers. These new challenges that marketing faces led to the necessity of including these influential but also potentially risky instruments to the disposal of companies, taking advantage of the huge volume of data that is within these networks. However, there are privacy issues that should be taken into account. In order to create a strong relationship with the consumers, it is necessary to listen, first; to study what it is being said on social media, the social media listening. It is, indeed, crucial to know what is said to be able to make marketing strategies that will allow the creation of strong and lasting relationships. For that, there are appropriate tools, on which social media listening is based. The internship at EDP appeared in this context. Following the action-research methodology, this internship’s goal was to analyse the content of conversations being held about the company, in order to reveal important insights to EDP. This has resulted in a monthly report that accounts for specific digital metrics; mainly mention counting and sentiment analysis. The importance of this study is justified by the theme’s currentness and the scarce scientific literature about it. Its scope is to present a model of report that aims to help companies develop strategies based on this new data, particularly in the marketing field.N/
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