Content analysis model to analyze facets of social mission of public library on the Facebook and in the websites

In this paper we present the development and the implementation of a content analysis model for observing aspects relating to the social mission of the public library on Facebook pages and websites. The model is unique and it was developed from the literature. There were designed the four categories for analysis Generate social capital and social cohesion, Consolidate democracy and citizenship, Social and digital inclusion and Fighting illiteracies. The model enabled the collection and the analysis of data applied to a case study consisting of 99 Portuguese public libraries with Facebook page. With this model of content analysis we observed the facets of social mission and we read the actions with social facets on the Facebook page and in the websites of public libraries. At the end we discuss in parallel the results of observation of the Facebook of libraries and the websites. By reading the description of the actions of the social mission, the general conclusion and the most immediate is that 99 public libraries on Facebook and websites rarely publish social character actions, and the results are little satisfying. The Portuguese public libraries highlight substantially the actions in the category Generate social capital and social cohesion.

Socially Constructed Environmental Issues and Sport: A Content Analysis of Ski Resort Environmental Communications

Due to the impact of sport on the natural environment (UN, 2010), it is important to examine the interplay between environmental issues and sport (Hums, 2010, Mallen & Chard, 2011; Nauright & Pope, 2009; Ziegler, 2007). This research content analyzed 82 ski resort environmental communications (SRECs). These communications were rated for their prominence, breadth, and depth using the delineation of environmental issues provided by the Sustainable Slopes Program (SSP) Charter. This data was compared to the resorts’ degree of environmentally responsible action as rated by the Ski Area Citizens’ Coalition (SACC). An adaptation of Hudson and Miller's (2005) model was then used to classify the ski resorts as inactive, reactive, exploitive, or proactive in their environmental activities. Recommendations have been made for standardization and transparency in environmental disclosures and an environmental management system to aid ski resorts in moving from ad hoc processes to a systematic and comprehensive framework for improving environmental performance.

Originator or propagator? Incorporating social role theory into topic models for twitter content analysis

A large number of studies have been devoted to modeling the contents and interactions between users on Twitter. In this paper, we propose a method inspired from Social Role Theory (SRT), which assumes that a user behaves differently in different roles in the generation process of Twitter content. We consider the two most distinctive social roles on Twitter: originator and propagator, who respectively posts original messages and retweets or forwards the messages from others. In addition, we also consider role-specific social interactions, especially implicit interactions between users who share some common interests. All the above elements are integrated into a novel regularized topic model. We evaluate the proposed method on real Twitter data. The results show that our method is more effective than the existing ones which do not distinguish social roles. Copyright 2013 ACM.

Incorporating social role theory into topic models for social media content analysis

In this paper, we explore the idea of social role theory (SRT) and propose a novel regularized topic model which incorporates SRT into the generative process of social media content. We assume that a user can play multiple social roles, and each social role serves to fulfil different duties and is associated with a role-driven distribution over latent topics. In particular, we focus on social roles corresponding to the most common social activities on social networks. Our model is instantiated on microblogs, i.e., Twitter and community question-answering (cQA), i.e., Yahoo! Answers, where social roles on Twitter include "originators" and "propagators", and roles on cQA are "askers" and "answerers". Both explicit and implicit interactions between users are taken into account and modeled as regularization factors. To evaluate the performance of our proposed method, we have conducted extensive experiments on two Twitter datasets and two cQA datasets. Furthermore, we also consider multi-role modeling for scientific papers where an author's research expertise area is considered as a social role. A novel application of detecting users' research interests through topical keyword labeling based on the results of our multi-role model has been presented. The evaluation results have shown the feasibility and effectiveness of our model.

Screening for leprosy in immigrants: A decision analysis model

Almost all leprosy cases reported in industrialized countries occur amongst immigrants or refugees from developing countries where leprosy continues to be an important health issue. Screening for leprosy is an important question for governments in countries with immigration and refugee programmes. A decision analysis framework is used to evaluate leprosy screening. The analysis uses a set of criteria and parameters regarding leprosy screening, and available data to estimate the number of cases which would be detected by a leprosy screening programme of immigrants from countries with different leprosy prevalences, compared with a policy of waiting for immigrants who develop symptomatic clinical diseases to present for health care. In a cohort of 100,000 immigrants from high leprosy prevalence regions (3.6/10,000), screening would detect 32 of the 42 cases which would arise in the destination country over the 14 years after migration; from medium prevalence areas (0.7/10,000) 6.3 of the total 8.1 cases would be detected, and from low prevalence regions (0.2/10,600) 1.8 of 2.3 cases. Using Australian data, the migrant mix would produce 74 leprosy cases from 10 years intake; screening would detect 54, and 19 would be diagnosed subsequently after migration. Screening would only produce significant case-yield amongst immigrants from regions or social groups with high leprosy prevalence. Since the number of immigrants to Australia from countries of higher endemnicity is not large routine leprosy screening would have a small impact on case incidence.

Data analysis model selection for estimating local population size of the Risso’s dolphin (Grampus griseus) in the Azores

27th Annual Conference of the European Cetacean Society. Setúbal, Portugal, 8-10 April 2013.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.

The Patientʼs Perception of Eosinophilic Esophagitis Related Symptoms: a Qualitative Content Analysis

Background and Aims: The international EEsAI study group is currently developing an activity index for Eosinophilic Esophagitis (EoE). A potential discrepancy between patient and physician reported EoE symptoms has not been assessed yet. Therefore, we aimed to evaluate patient reported items describing their EoE activity and to compare these with the physicianʼs perception. Methods: A questionnaire was sent to 100 EoE patients in Switzerland. EoE-related symptoms dependent and independent of food intake were reported by patients. Results were analyzed using a qualitative content analysis and compared with symptoms reported by international EoE experts in Delphi rounds. Results: The questionnaire response rate was 64/100. The following items were developed by combining categories based on patients answers: food-consistency related dysphagia, frequency and severity of dysphagia, food impaction, strategies to avoid food impaction, food allergy, drinking-related retrosternal pain. The following food categories associated with dysphagia were identified: meat, rice, dry bread, French fries, raw, fibrous foods, others. Sports and psychological stress were identified as triggers for non-food intake related EoE symptoms. A good correlation was found between patient and physicianʼs reported EoE related symptoms. Conclusions: There is a good correlation between patient reported symptoms and the physicianʼs perception of clinical items as reported by international EoE experts. These patient reported outcomes will now be incorporated into the EEsAI questionnaire that measures EoE activity.

Inter-rater Reliability of Criteria-Based Content Analysis of Children's Statements of Abuse.

The evaluation of children's statements of sexual abuse cases in forensic cases is critically important and must and reliable. Criteria-based content analysis (CBCA) is the main component of the statement validity assessment (SVA), which is the most frequently used approach in this setting. This study investigated the inter-rater reliability (IRR) of CBCA in a forensic context. Three independent raters evaluated the transcripts of 95 statements of sexual abuse. IRR was calculated for each criterion, total score, and overall evaluation. The IRR was variable for the criteria, with several being unsatisfactory. But high IRR was found for the total CBCA scores (Kendall's W = 0.84) and for overall evaluation (Kendall's W = 0.65). Despite some shortcomings, SVA remains a robust method to be used in the comprehensive evaluation of children's statements of sexual abuse in the forensic setting. However, the low IRR of some CBCA criteria could justify some technical improvements.

Dynamic Analysis Model of Spherical Roller Bearings with Defects

Rolling element bearings are essential components of rotating machinery. The spherical roller bearing (SRB) is one variant seeing increasing use, because it is self-aligning and can support high loads. It is becoming increasingly important to understand how the SRB responds dynamically under a variety of conditions. This doctoral dissertation introduces a computationally efficient, three-degree-of-freedom, SRB model that was developed to predict the transient dynamic behaviors of a rotor-SRB system. In the model, bearing forces and deflections were calculated as a function of contact deformation and bearing geometry parameters according to nonlinear Hertzian contact theory. The results reveal how some of the more important parameters; such as diametral clearance, the number of rollers, and osculation number; influence ultimate bearing performance. Distributed defects, such as the waviness of the inner and outer ring, and localized defects, such as inner and outer ring defects, are taken into consideration in the proposed model. Simulation results were verified with results obtained by applying the formula for the spherical roller bearing radial deflection and the commercial bearing analysis software. Following model verification, a numerical simulation was carried out successfully for a full rotor-bearing system to demonstrate the application of this newly developed SRB model in a typical real world analysis. Accuracy of the model was verified by comparing measured to predicted behaviors for equivalent systems.

Dynamic Competitor Analysis Model Of Welding Quality Management Software

Tämä diplomityö arvioi hitsauksen laadunhallintaohjelmistomarkkinoiden kilpailijoita. Kilpailukenttä on uusi ja ei ole tarkkaa tietoa siitä minkälaisia kilpailijoita on markkinoilla. Hitsauksen laadunhallintaohjelmisto auttaa yrityksiä takaamaan korkean laadun. Ohjelmisto takaa korkean laadun varmistamalla, että hitsaaja on pätevä, hän noudattaa hitsausohjeita ja annettuja parametreja. Sen lisäksi ohjelmisto kerää kaiken tiedon hitsausprosessista ja luo siitä vaadittavat dokumentit. Diplomityön teoriaosuus muodostuu kirjallisuuskatsauksesta ratkaisuliike-toimintaan, kilpailija-analyysin ja kilpailuvoimien teoriaan sekä hitsauksen laadunhallintaan. Työn empiriaosuus on laadullinen tutkimus, jossa tutkitaan kilpailevia hitsauksen laadunhallintaohjelmistoja ja haastatellaan ohjelmistojen käyttäjiä. Diplomityön tuloksena saadaan uusi kilpailija-analyysimalli hitsauksen laadunhallintaohjelmistoille. Mallin avulla voidaan arvostella ohjelmistot niiden tarjoamien primääri- ja sekundääriominaisuuksien perusteella. Toiseksi tässä diplomityössä analysoidaan nykyinen kilpailijatilanne hyödyntämällä juuri kehitettyä kilpailija-analyysimallia.