A linguagem no Twitter: um enfoque sistêmico-funcional

O objetivo deste trabalho é investigar as características da linguagem no Twitter, focalizando (i) seu propósito comunicativo, (ii) seus participantes discursivos e (iii) suas relações interpessoais. Por acreditar que a linguagem é um recurso sistemático e que somente através dela expressamos significados em determinados contextos, encontramos na Linguística Sistêmico-Funcional (LSF) uma base teórica que se encaixa à pesquisa. Para Halliday(1994), a linguística é o estudo de como as pessoas negociam sentido através do uso da linguagem. Assim, encontramos no Twitter, um corpus diversificado que reforça ainda mais a teoria da LSF, quando afirma sermos nós, falantes da língua, os únicos responsáveis por nossas escolhas lexicais, tendo consciência de como e onde, contextualmente falando, podemos aplicar em uma atividade linguística em que estivermos engajados. O material de pesquisa foi constituído mediante a coleta inicial de 671 comentários postados no Twitter em 2010. Dados obtidos a partir da análise desta coleta confirmam o argumento de Crystal (2011), de que a expressão de opinião é o principal propósito comunicativo das mensagens postadas no microblogging. Assim, após recortes no corpus para coleta exclusivamente de opiniões, 201 tuítes resultantes de duas coletas realizadas em datas e situações diferentes foram analisados: uma, após notícia de agressão a uma professora; a segunda, momentos antes e durante a Copa Mundial de 2010. Os resultados apontam diferenças entre as amostras, principalmente em função de aspectos do contexto de situação: pois embora o tom seja de indignação nas amostras com tuítes opinativos, apenas na amostra futebol há tentativa de se orientar a ação do outro. Quanto às relações interpessoais, foram identificadas marcas de interação face a face nas duas amostras, mas apenas na amostra futebol identificou-se uso de linguagem de baixo calão. Finalmente, em relação às características gerais do Twitter, observa-se o uso de linguagem reduzida na forma de caracteres emotivos ou de abreviações, o uso de interjeições e pontos de exclamação. Observou-se ainda o uso recorrente de léxico valorativo, de ironia e de perguntas retóricas para expressão de indignação, mas estes traços parecem ser afetados por aspectos do contexto de situação, mais do que por características do Twitter

Expressing Sentiments in Game Reviews

Opinion mining and sentiment analysis are important research areas of Natural Language Processing (NLP) tools and have become viable alternatives for automatically extracting the affective information found in texts. Our aim is to build an NLP model to analyze gamers’ sentiments and opinions expressed in a corpus of 9750 game reviews. A Principal Component Analysis using sentiment analysis features explained 51.2 % of the variance of the reviews and provides an integrated view of the major sentiment and topic related dimensions expressed in game reviews. A Discriminant Function Analysis based on the emerging components classified game reviews into positive, neutral and negative ratings with a 55 % accuracy.

Marketing to change public opinion on climate change : a case study

Corporate advertisers spend far greater budgets than any social marketing campaign and have great potential to change public opinion on the urgent need for action on climate change. However “green-washing” has become a widespread practice by companies that wish to appear to be socially responsible without a genuine commitment and consumers can be very cynical about green marketing campaigns. Can companies be climate change advocates and still satisfy shareholders? This paper offers a case study on an Australian insurance company that argues it can make money from doing the right thing.

Critical opinion : the Docklands Precinct

Every one and their dog has done a Docklands design studio at university if they were educated in Melbourne. And all designers have an opinion on the idea of Docklands and its potential in the future, but few, apart from the Docklands authority themselves, have a handle on what's going on there now and what constitutes its qualities.

State-of-the-Art Review on Opinion Mining from Online Customers’ Feedback

Dealing with the ever-growing information overload in the Internet, Recommender Systems are widely used online to suggest potential customers item they may like or find useful. Collaborative Filtering is the most popular techniques for Recommender Systems which collects opinions from customers in the form of ratings on items, services or service providers. In addition to the customer rating about a service provider, there is also a good number of online customer feedback information available over the Internet as customer reviews, comments, newsgroups post, discussion forums or blogs which is collectively called user generated contents. This information can be used to generate the public reputation of the service providers’. To do this, data mining techniques, specially recently emerged opinion mining could be a useful tool. In this paper we present a state of the art review of Opinion Mining from online customer feedback. We critically evaluate the existing work and expose cutting edge area of interest in opinion mining. We also classify the approaches taken by different researchers into several categories and sub-categories. Each of those steps is analyzed with their strength and limitations in this paper.

Inducing shades of meaning by matrix methods : a first step towards thematic analysis of opinion

This article explores two matrix methods to induce the ``shades of meaning" (SoM) of a word. A matrix representation of a word is computed from a corpus of traces based on the given word. Non-negative Matrix Factorisation (NMF) and Singular Value Decomposition (SVD) compute a set of vectors corresponding to a potential shade of meaning. The two methods were evaluated based on loss of conditional entropy with respect to two sets of manually tagged data. One set reflects concepts generally appearing in text, and the second set comprises words used for investigations into word sense disambiguation. Results show that for NMF consistently outperforms SVD for inducing both SoM of general concepts as well as word senses. The problem of inducing the shades of meaning of a word is more subtle than that of word sense induction and hence relevant to thematic analysis of opinion where nuances of opinion can arise.

Queering cyberspace : fan fiction communities as spaces for expressing and exploring sexuality

The social construction of sexuality over the past one hundred and fifty years has created a dichotomy between heterosexual and non-heterosexual identities that essentially positions the former as “normal” and the latter as deviant. Even Kinsey’s and others’ work on the continuum of sexualities did little to alter the predominantly heterosexist perception of the non-heterosexual as “other” (Kinsey, Pomeroy and Martin 2007; Esterberg 2006; Franceour and Noonan 2007). Some political action and academic work is beginning to challenge such perceptions. Even some avenues of social interaction, such as the recent proliferation of online communities, may also challenge such views, or at least contribute to their being rethought in some ways. This chapter explores a specific kind of online community devoted to fan fiction, specifically homoerotic – or what is known colloquially as “slash” – fan fiction. Fan fiction is fiction, published on the internet, and written by fans of well-known books and television shows, using the characters to create new and varied plots. “Slash” refers to the pairing of two of the male characters in a romantic relationship, and the term comes from the punctuation mark dividing the named pair as, for example, Spock/Kirk from the Star Trek television series. Although there are some slash fan-fiction stories devoted to female-female relationships – called “femmeslash” – the term “slash” generally refers to male-male relationships, and will be utilized throughout this chapter, given that the research discussed focuses on communities centered around one such male pairing.

How useful is expert opinion for predicting the distribution of a species within and beyond the region of expertise? A case study using brush-tailed rock-wallabiesPetrogale penicillata

1. Species' distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species' distribution information is expert opinion. This study evaluates expert knowledge and its source. In particular, we determine whether models built on expert knowledge apply over multiple regions or only within the region where the knowledge was derived. 2. The case study focuses on the distribution of the brush-tailed rock-wallaby Petrogale penicillata in eastern Australia. We brought together from two biogeographically different regions substantial and well-designed field data and knowledge from nine experts. We used a novel elicitation tool within a geographical information system to systematically collect expert opinions. The tool utilized an indirect approach to elicitation, asking experts simpler questions about observable rather than abstract quantities, with measures in place to identify uncertainty and offer feedback. Bayesian analysis was used to combine field data and expert knowledge in each region to determine: (i) how expert opinion affected models based on field data and (ii) how similar expert-informed models were within regions and across regions. 3. The elicitation tool effectively captured the experts' opinions and their uncertainties. Experts were comfortable with the map-based elicitation approach used, especially with graphical feedback. Experts tended to predict lower values of species occurrence compared with field data. 4. Across experts, consensus on effect sizes occurred for several habitat variables. Expert opinion generally influenced predictions from field data. However, south-east Queensland and north-east New South Wales experts had different opinions on the influence of elevation and geology, with these differences attributable to geological differences between these regions. 5. Synthesis and applications. When formulated as priors in Bayesian analysis, expert opinion is useful for modifying or strengthening patterns exhibited by empirical data sets that are limited in size or scope. Nevertheless, the ability of an expert to extrapolate beyond their region of knowledge may be poor. Hence there is significant merit in obtaining information from local experts when compiling species' distribution models across several regions.

The effects of pore architecture in silk fibroin scaffolds on the growth and differentiation of mesenchymal stem cells expressing BMP7

The pore architecture of scaffolds is known to play a critical role in tissue engineering as it provides the vital framework for seeded cells to organize into a functioning tissue. In this report we have investigated the effects of different concentrations of silk fibroin protein on three-dimensional (3D) scaffold pore microstructure. Four pore size ranges of silk fibroin scaffolds were made by the freeze drying technique, with the pore sizes ranging from 50 to 300 lm. The pore sizes of the scaffolds decreased as the concentration of fibroin protein increased. Human bone marrow mesenchymal stromal cells (BMSC) transfected with the BMP7 gene were cultured in these scaffolds. A cell viability colorimetric assay, alkaline phosphatase assay and reverse transcription-polymerase chain reaction were performed to analyze the effect of pore size on cell growth, the secretion of extracellular matrix (ECM) and osteogenic differentiation. Cell migration in 3D scaffolds was confirmed by confocal microscopy. Calvarial defects in SCID mice were used to determine the bone forming ability of the silk fibroin scaffolds incorporating BMSC expressing BMP7. The results showed that BMSC expressing BMP7 preferred a pore size between 100 and 300 lm in silk fibroin protein fabricated scaffolds, with better cell proliferation and ECM production. Furthermore, in vivo transplantation of the silk fibroin scaffolds combined with BMSC expressing BMP7 induced new bone formation. This study has shown that an optimized pore architecture of silk fibroin scaffolds can modulate the bioactivity of BMP7-transfected BMSC in bone formation.

The effects of pore architecture in silk fibroin scaffolds on the growth and differentiation of BMP7-expressing mesenchymal stem cells

Pore architecture of scaffolds is known to play a critical role in tissue engineering as it provides the vital framework for the seeded cells to organize into a functioning tissue. In this report, we investigated the effects of different concentration on silk fibroin protein 3D scaffold pore microstructure. Four pore size ranges of silk fibroin scaffolds were made by freeze-dry technique, with the pore sizes ranging from 50 to 300 µm. The pore size of the scaffold decreases as the concentration increases. Human mesenchymal stem cells were in vitro cultured in these scaffolds. After BMP7 gene transferred, DNA assay, ALP assay, hematoxylin–eosin staining, alizarin red staining and reverse transcription-polymerase chain reaction were performed to analyze the effect of the pore size on cell growth, differentiation and the secretion of extracellular matrix (ECM). Cell morphology in these 3D scaffolds was investigated by confocal microscopy. This study indicates mesenchymal stem cells prefer the group of scaffolds with pore size between 100 and 300 µm for better proliferation and ECM production

Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline.