Identification and monitoring polarization from social network perspective

Abstract. Polarization is a new phenomenon that threatens the cohesion and social development of our society. The raise of social media is known to have contributed significantly to the emergence of this phenomenon as it can be noticed from the multiplication of far right and racist online communities as well as the ill-structured political discourse. This can be noticed from scrutinizing recent US or EU elections. Automatic identification of polarization from social media plays a key role in devising appropriate defence strategy to tackle the issue and avoid escalation. This thesis implements several methods to identify polarization from Twitter data issued from Trump-Clinton US election campaign using metrics like Belief Polarization Index (BPI) and Sentiment Analysis. Furtherly, semantic role labelling and argument mining were applied to derive structure of arguments of polarized discourse. Especially, we constructed thirteen topics of interests that were used as potential candidates for polarized discourse. For each topic, the cosine distance of the frequency of the topic overtime between the two candidates was used to indicate the polarization (called as Belief Polarization Index). The statistics inference of sentiment scores was implemented to convey either a positive or negative polarity, which are then further examined using argument structure. All the proposed approaches provide attempts to measure the polarization between two individuals from different perspectives, which may give some hints or references for future research.Tiivistelmä. Polarisaatio on uusi ilmiö, joka uhkaa yhteiskuntamme yhteenkuuluvuutta ja sosiaalista kehitystä. Sosiaalisen median nousun tiedetään vaikuttaneen merkittävästi tämän ilmiön syntymiseen, koska se voidaan havaita äärioikeistolaisten ja rasististen verkkoyhteisöjen lisääntymisestä sekä huonosti jäsennellystä poliittisesta keskustelusta. Tämä voidaan havaita tarkastelemalla äskettäisiä Yhdysvaltojen tai EU: n vaaleja. Polarisaation automaattisella tunnistamisella sosiaalisesta mediasta on keskeinen rooli sopivan puolustusstrategian suunnittelussa ongelman ratkaisemiseksi ja eskalaation välttämiseksi. Tässä opinnäytetyössä toteutetaan useita menetelmiä polarisaation tunnistamiseksi Yhdysvaltain Trump-Clintonin vaalikampanjan Twitter-tiedoista käyttämällä mittareita, kuten vakaumuspolarisaatio indeksi (BPI) ja mielipiteiden analyysi. Lisäksi semanttisen roolin merkintöjä ja argumenttien louhintaa sovellettiin polarisoidun diskurssin argumenttien rakenteen johtamiseen. Erityisesti rakensimme kolmetoista aihepiiriä, joita käytettiin potentiaalisina ehdokkaina polarisoituneeseen keskusteluun. Kunkin aiheen kohdalla kahden ehdokkaan aiheiden ylityötiheyden kosinietäisyyttä käytettiin osoittamaan polarisaatiota (kutsutaan nimellä Belief Polarization Index). Tunnelmapisteiden tilastollinen päättely toteutettiin joko positiivisen tai negatiivisen napaisuuden välittämiseksi, joita sitten tutkitaan edelleen argumenttirakennetta käyttäen. Kaikki ehdotetut lähestymistavat tarjoavat yrityksiä mitata kahden ihmisen välistä polarisaatiota eri näkökulmista, mikä saattaa antaa vihjeitä tai viitteitä tulevaa tutkimusta varten

Business Process Retrieval Based on Behavioral Semantics

This paper develops a framework for retrieving business processes considering search requirements based on behavioral semantics properties; it presents a framework called "BeMantics" for retrieving business processes based on structural, linguistics, and behavioral semantics properties. The relevance of the framework is evaluated retrieving business processes from a repository, and collecting a set of relevant business processes manually issued by human judges. The "BeMantics" framework scored high precision values (0.717) but low recall values (0.558), which implies that even when the framework avoided false negatives, it prone to false positives. The highest pre- cision value was scored in the linguistic criterion showing that using semantic inference in the tasks comparison allowed to reduce around 23.6 % the number of false positives. Using semantic inference to compare tasks of business processes can improve the precision; but if the ontologies are from narrow and specific domains, they limit the semantic expressiveness obtained with ontologies from more general domains. Regarding the perform- ance, it can be improved by using a filter phase which indexes business processes taking into account behavioral semantics propertie

Recursion Aware Modeling and Discovery For Hierarchical Software Event Log Analysis (Extended)

This extended paper presents 1) a novel hierarchy and recursion extension to the process tree model; and 2) the first, recursion aware process model discovery technique that leverages hierarchical information in event logs, typically available for software systems. This technique allows us to analyze the operational processes of software systems under real-life conditions at multiple levels of granularity. The work can be positioned in-between reverse engineering and process mining. An implementation of the proposed approach is available as a ProM plugin. Experimental results based on real-life (software) event logs demonstrate the feasibility and usefulness of the approach and show the huge potential to speed up discovery by exploiting the available hierarchy.Comment: Extended version (14 pages total) of the paper Recursion Aware Modeling and Discovery For Hierarchical Software Event Log Analysis. This Technical Report version includes the guarantee proofs for the proposed discovery algorithm

A Conceptualization and Operationalization of Process Visibility Capabilities

Lately, a trend towards real-time, process-centric Business Intelligence & Analytics on the operational level has emerged. Although there are various systems such as BAM, BPI or CEP that claim to deliver visibility for operational processes, the underlying capabilities remain vague. To close this research gap we present a conceptualization and operationalization for process visibility capabilities. We use the results of a literature analysis and expert interviews for the conceptualization of the respective capabilities. The operationalization is based on existing literature and refined in two academic feedback sessions as well as one card sorting procedure with experts from practice. Our results contribute to a better understanding which capabilities create process visibility and provide a basis for future research

Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques

The goal of QoS-aware service composition is to generate optimal composite services that satisfy the QoS requirements defined by clients. However, when compositions contain more than one execution path (i.e., multiple path's compositions), it is difficult to generate a composite service that simultaneously optimizes all the execution paths involved in the composite service at the same time while meeting the QoS requirements. This issue brings us to the challenge of solving the QoS-aware service composition problem, so called an optimization problem. A further research challenge is the determination of the QoS characteristics that can be considered as selection criteria. In this thesis, a smart QoS-aware service composition approach is proposed. The aim is to solve the above-mentioned problems via an optimization mechanism based upon the combination between runtime path prediction method and heuristic algorithms. This mechanism is performed in two steps. First, the runtime path prediction method predicts, at runtime, and just before the actual composition, execution, the execution path that will potentially be executed. Second, both the constructive procedure (CP) and the complementary procedure (CCP) heuristic algorithms computed the optimization considering only the execution path that has been predicted by the runtime path prediction method for criteria selection, eight QoS characteristics are suggested after investigating related works on the area of web service and web service composition. Furthermore, prioritizing the selected QoS criteria is suggested in order to assist clients when choosing the right criteria. Experiments via WEKA tool and simulation prototype were conducted to evaluate the methods used. For the runtime path prediction method, the results showed that the path prediction method achieved promising prediction accuracy, and the number of paths involved in the prediction did not affect the accuracy. For the optimization mechanism, the evaluation was conducted by comparing the mechanism with relevant optimization techniques. The simulation results showed that the proposed optimization mechanism outperforms the relevant optimization techniques by (1) generating the highest overall QoS ratio solutions, (2) consuming the smallest computation time, and (3) producing the lowest percentage of constraints violated number

Equity research: group Inditex

A company valuation is a complex process that requires a rich set of assumptions from the analyst – understanding the mechanisms behind valuation is crucial to make value-added decisions. The aim of this thesis is to value Inditex, one of the world´s largest fashion retailers. For this end, different valuation methodologies are described, used and compared, (the reasons concerning them will be explained), combining the academic approach with the most used practices in the valuation market. The equivalence between different discounted cash flow methods (such as the weighted average cost of capital, the adjusted present value, and the flow to equity) is an element of pedagogical interest in this master’s final work. Finally, the valuation result obtained will be subject to sensitivity analysis, to comparison with the traded market value, and comparison with the results obtained from a well-known Portuguese investment bank (Banco Português de Investimento), evidencing the main differences between both analysis.III Rita Tiago Rebelo II. RESUMO A avaliação de empresas é um processo complexo que requer a definição de um vasto conjunto de pressupostos pelo analista. A compreensão dos mecanismos de suporte de uma avaliação é fundamental para que possam ser tomadas decisões de valor acrescentado. O objectivo desta tese é avaliar o Grupo Inditex, um dos maiores retalhistas de moda do mundo. Para este fim foram descritas, analisadas, aplicadas e comparadas diferentes metodologias de avaliação (as razões subjacentes a cada uma serão apresentadas), combinando a abordagem académica com as práticas mais utilizadas no mercado de avaliações. A equivalência existente entre os diversos métodos de discounted cash flow (tais como o weighted average cost of capital, o adjusted present value, e o flow to equity) é um elemento de interesse pedagógico neste trabalho final de mestrado. Por último, o resultado obtido da avaliação será sujeito a análises de sensibilidade, a comparações com o valor de mercado e com os resultados obtidos por um conhecido banco de investimento Português (Banco Português de Investimento), evidenciando as principais diferenças entre ambas as análises

Measuring Infringement of Intellectual Property Rights

© Crown Copyright 2014. You may re-use this information (excluding logos) free of charge in any format or medium, under the terms of the Open Government Licence. To view this licence, visit http://www.nationalarchives.gov. uk/doc/open-government-licence/ Where we have identified any third party copyright information you will need to obtain permission from the copyright holders concernedThe review is wide-ranging in scope and overall our findings evidence a lack of appreciation among those producing research for the high-level principles of measurement and assessment of scale. To date, the approaches adopted by industry seem more designed for internal consumption and are usually contingent on particular technologies and/or sector perspectives. Typically, there is a lack of transparency in the methodologies and data used to form the basis of claims, making much of this an unreliable basis for policy formulation. The research approaches we found are characterised by a number of features that can be summarised as a preference for reactive approaches that look to establish snapshots of an important issue at the time of investigation. Most studies are ad hoc in nature and on the whole we found a lack of sustained longitudinal approaches that would develop the appreciation of change. Typically the studies are designed to address specific hypotheses that might serve to support the position of the particular commissioning body. To help bring some structure to this area, we propose a framework for the assessment of the volume of infringement in each different area. The underlying aim is to draw out a common approach wherever possible in each area, rather than being drawn initially to the differences in each field. We advocate on-going survey tracking of the attitudes, perceptions and, where practical, behaviours of both perpetrators and claimants in IP infringement. Clearly, the nature of perpetrators, claimants and enforcement differs within each IPR but in our view the assessment for each IPR should include all of these elements. It is important to clarify that the key element of the survey structure is the adoption of a survey sampling methodology and smaller volumes of representative participation. Once selection is given the appropriate priority, a traditional offline survey will have a part to play, but as the opportunity arises, new technological methodologies, particularly for the voluntary monitoring of online behaviour, can add additional detail to the overall assessment of the scale of activity. This framework can be applied within each of the IP right sectors: copyright, trademarks,patents, and design rights. It may well be that the costs involved with this common approach could be mitigated by a syndicated approach to the survey elements. Indeed, a syndicated approach has a number of advantages in addition to cost. It could be designed to reduce any tendency either to hide inappropriate/illegal activity or alternatively exaggerate its volume to fit with the theme of the survey. It also has the scope to allow for monthly assessments of attitudes rather than being vulnerable to unmeasured seasonal impacts

Advanced Auditing of Run-Time Conflicts in Declarative Process Models using Time Series Clustering

We present a novel approach for auditing conflicts between declarative constraints that arise during process execution, i.e., relative to observed traces. As a main advantage, taking a post-execution perspective allows to consider all observed traces and their interrelations, and to assess conflicts from a global perspective. Our approach allows to classify and prioritize conflicts as a basis for re-modelling, e.g., which conflicts are an outlier, and which require an urgent change to the model. Also, our approach provides means for quantitative root-cause analysis, i.e., prioritizing which rules need to be changed. We implement our approach and show that it can be applied in settings of industrial scale by means of runtime experiments with real-life data-sets

Methods and Models for Industrial Internet of Things-based Business Process Improvement

Over the last three decades, the Internet of Things (IoT) has gained significant importance and has been implemented in many private, public, and business contexts. Leveraging and combining the IoT's capabilities enables far-reaching transformations and disruptive innovations that are increasingly recognized, especially by industrial organizations. In this regard, the Industrial IoT (IIoT) paradigm has emerged, describing the use of IIoT technology in the industrial domain. One key use of the IIoT is the incremental or radical improvement of business processes. This goal-oriented change of business processes with IIoT technology to accomplish organizational goals more effectively is called IIoT-based Business Process Improvement (BPI). Many use cases demonstrate the benefits of IIoT-based BPI for all types of industrial organizations. However, the interconnection between IIoT and BPI lacks theoretical knowledge and applicable artifacts that support practitioners. Moreover, a significant number of related projects fail or do not achieve the anticipated benefits. This issue has drawn attention in recent scholarly literature, which calls for further research. The dissertation at hand approaches this research gap by extending and advancing existing knowledge and providing valuable contributions to managerial practice. Three critical challenges for conducting IIoT-based BPI projects are addressed in particular: First, the essential characteristics of IIoT-based BPI applications are explored. This enables their classification and a foundational comprehension of the research field. Second, the required capabilities to leverage IIoT for BPI are identified. On this basis, industrial organizations can assess their maturity and readiness for implementing corresponding applications. Third, the identification, specification, and selection of appropriate applications are addressed. These activities enable the successful practical execution of IIoT projects with BPI potential