Exploration of implicit theories in the formation of expert opinion in portuguese criminal law

This dissertation examines different aspects involved in the formation of psychologists’ expert opinion in the Portuguese criminal justice system, more precisely, as this opinion is reflected in assessment reports. The present dissertation is comprised of three qualitative studies, the first sought to provide a general portrait of a sample of 106 forensic psychological reports as to their overall quality as measured in terms of relevance and coherence. Results show that the formal markers of quality are present in the sample analysed, a certain number of weaknesses have been observed, notably concerning the internal coherence of the reports as well as the relevance of the information reported on. The second study explored the opinions of 17 Portuguese judges and state prosecutors concerning the use they make of this type of forensic report. It appears that they consider these reports to be useful and very credible, specially so when they have been produced under the auspices of the National Institute of Legal Medicine and Forensic Sciences, which is the state forensic institution. Furthermore, it appears that judges and prosecutors were particularly interested in data that allowed for a personalised portrait of the assessee. The third study sought to better comprehend the conceptual bases on which psychologists construct their reports. To this end, an exploratory study was undertaken with a sample of key-actors; the analysis of their interviews shows that they define their judicial mandate as well as the basic concepts that are associated to this mandate in different ways. A theoretical framework provided by an implicit theories model was used to help understand these results.

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.

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.

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.

Integration of opinion into customer analysis model

Nowadays, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes. A use case study is also presented in this paper to show the advantages of using OLAP and data cubes to analyze costumers’ opinions.

User interface design for social web theme and opinion analysis

The Social Web is a torrent of real-time information and an emerging discipline is now focussed on harnessing this information flow for analysis of themes, opinions and sentiment. This short paper reports on early work on designing better user interfaces for end users in manipulating the outcomes from these analysis engines.

Equity for taxpayers within Australia’s retirement savings regime : a dissenting opinion

This article asks the question whether Australia’s retirement savings regime, specifically the superannuation component and the attached taxation concessions, is a regime which is equitable to all taxpayers. In a dissenting opinion, it is argued that the current regime, along with the changes proposed by the Federal Government in its response to the Henry Review, does not result in a retirement savings regime which benefits all taxpayers equally. As such, it is suggested that the only way to ensure an equitable regime is to incorporate a gender perspective into public finance analysis to determine how the retirement savings policies affect women and men differently. In doing so, a specific tax policy which provides for additional, fiscally significant concessions for taxpayers who do not fit the criteria of a ‘normal’ taxpayer, that is a taxpayer working as an employee in a full time position for an uninterrupted 35 years, should be incorporated into Australia’s current fiscal policy.

Speed enforcement in Australia : a changing policy landscape shaped by public opinion

- Speeding and crash involvement in Australia - Speed management in Australia - Jurisdictional differences - National Road Safety Strategy (2011-2020) - Auditor-General reviews of speed camera programs - The role of public opinion/feedback - Implications for speed management