60 research outputs found
Inquest of Current Situation in Afghanistan Under Taliban Rule Using Sentiment Analysis and Volume Analysis
Microblogging websites and social media platforms serve as a potential source for mining public opinions and sentiments on a variety of subjects including the prevailing situations in war-afflicted countries. In particular, Twitter has a large number of geotagged tweets that make the analysis of sentiments across time and space possible. This study performs volume analysis and sentiment analysis using LDA (Latent Dirichlet Allocation) and text mining over two datasets collected for different periods. To increase the adequacy and efficacy of the sentiment analysis, a hybrid feature engineering approach is proposed that elevates the performance of machine learning models. Geotagged tweets are used for volume analysis indicating that the highest number of tweets is originated from India, the US, the UK, Pakistan, and Afghanistan. Analysis of positive and negative tweets reveals that negative tweets are mostly originated from India and the US. On the contrary, positive tweets belong to Pakistan and Afghanistan. LDA is used for topic modeling on two datasets containing tweets about the current situation after the Taliban take control of Afghanistan. Topics extracted through LDA suggest that majority of the Afghanistan people seem satisfied with the Taliban�s takeover while the topics from negative tweets reveal that issues discussed in negative tweets are related to the US concerns in Afghanistan. Sentiment analysis over two different datasets indicates that the trend of the sentiments has been shifted positively over three weeks
Racism Detection by Analyzing Differential Opinions Through Sentiment Analysis of Tweets Using Stacked Ensemble GCR-NN Model
With social media's dominating role in the socio-political landscape, several existing and new forms of racism took place on social media. Racism has emerged on social media in different forms, both hidden and open, hidden with the use of memes and open as the racist remarks using fake identities to incite hatred, violence, and social instability. Although often associated with ethnicity, racism is now thriving based on color, origin, language, cultures, and most importantly religion. Social media opinions and remarks provocating racial differences have been regarded as a serious threat to social, political, and cultural stability and have threatened the peace of different countries. Consequently, social media being the leading source of racist opinions dissemination should be monitored and racism remarks should be detected and blocked timely. This study aims at detecting Tweets that contain racist text by performing the sentiment analysis of Tweets. Owing to the superior performance of deep learning, a stacked ensemble deep learning model is assembled by combining gated recurrent unit (GRU), convolutional neural networks (CNN), and recurrent neural networks RNN, called, Gated Convolutional Recurrent- Neural Networks (GCR-NN). GRU is on the top in the GCR-NN model to extract the suitable and prominent features from raw text, CNN extracts important features for RNN to make accurate predictions. Obviously, several experiments are conducted to investigate and analyze the performance of the proposed GCR-NN within the scope of machine learning and deep learning models indicating the superior performance of GCR-NN with increased 0.98 accuracy. The proposed GCR-NN model can detect 97% of the tweets that contain racist comments
Analisis Sentimen Produk Herbal Jamu pada Media Sosial Instagram
Meningkatnya kapasitas dan jumlah industri dan usaha kecil yang bergerak pada bidang herbal jamu di Indonesia mengindikasikan peningkatan dan perubahan gaya hidup masyarakat untuk mengkonsumsi tanaman obat [1]. Produk herbal jamu bagi sebagian besar masyarakat Indonesia telah dipercaya dan lebih aman dalam mengobati penyakit. Produk herbal jamu juga terbukti memberikan manfaat bagi perawatan penderita batu saluran kemih dan diabetes melitus [2][3]. Meski demikian, terdapat faktor lain seperti budaya dan kepercayaan dalam memilih obat herbal [4]. Pemasaran sebuah produk herbal jamu dengan memanfaatkan media sosial saat ini menjadi kebutuhan primer dan memiliki potensi untuk memperluas jangkauan pemasaran bahkan meningkatkan omset penjualan produk [5][6]. Pelaku usaha seperti UMKM juga telah menyertakan media sosial seperti facebook, dan instagram sebagai media pemasaran yang dirasa lebih mudah dalam penggunaannya [7]. Pelaku usaha dan industri herbal jamu dapat memanfaatkan kemudahan dan efisiensi dari media sosial dalam melakukan penjualan. Penelitian ini bertujuan untuk mengungkap sentimen pengguna media sosial Instagram terhadap tren penjualan herbal jamu. Hasil penelitian akan mengungkap signifikansi penggunaan media sosial Instagram pada pemasaran produk herbal jamu
Challenges and opportunities of low-code platforms for software development
The current energy and climate crisis emphasize the energy-efficiency knowledge gap as a
pressing problem. This is addressed in the report and the mobile application called EnMo, which
was developed as part of this field lab. Topics regarding gamification, big data analytics, and
low-code development were investigated. The findings provide the foundation for developing
the app and its mission as a solution to the problem. EnMo incentivizes users to reduce their
household energy consumption, by collecting user information and providing educational and
gamified content. Thus, EnMo enables consumers to change their behavior and reduce their
energy-efficiency knowledge gap.
This exposition discusses the challenges and opportunity of low-code platforms for software
development specifically. While speedy development, low maintenance and cost as well as low
transparency and customization were filtered out as advantages of low-code, potential vendor
lock-ins, black box issues and the fear of replacing software developers might present pitfalls
of the technology
Recommended from our members
Modeling Urban Venue Dynamics through Spatio-Temporal Metrics and Complex Networks
The ubiquity of GPS-enabled devices, mobile applications, and intelligent transportation systems have enabled opportunities to model the world at an unprecedented scale. Urban environments, in particular, have benefited from new data sources that provide granular representations of activities across space and time. As cities experienced a rise in urbanization, they also faced challenges in managing vehicle levels, congestion, and public transportation systems. Modeling these fast-paced changes through rich data from sources such as taxis, bikes, and trains has enabled prediction models capable of characterizing trends and forecasting future changes. Data-driven studies of urban mobility dynamics have been instrumental in helping deliver more contextual services to cities, support urban policy, and inform business decisions. This dissertation explores how novel algorithmic architectures and techniques reveal and predict business trends and urban development patterns.
The research informing this dissertation harnesses principles from network science, modeling cities as connected networks of venues. Building upon a foundation of research in complex network theory, urban computing, and machine learning, we propose algorithms tailored for three computing tasks focused on modeling venue dynamics, characteristics, and trends. First, we predict the demand for newly opened businesses using insights from movement patterns across different regions of the city. Through this analysis we demonstrate how temporally similar areas can be successfully used as inputs to predict the visitation patterns of new venues. Next, we forecast the likelihood of business failure through a supervised learning model. We analyze the value of varying features in predicting business failure and explore their impact across new and established venues and across different cities worldwide. Finally, we present a deep learning architecture which integrates both spatial and topological features to predict the future demand for a venue. These works highlight the power of complex network measures to quantify the structure of a city and inform prediction models.
This dissertation leverages vast amounts of data from spatio-temporal networks to model venue dynamics. The research puts forward evidence to support a data-driven study of geographic systems applied to fundamental questions in urban studies, retail development, and social science.Gates Cambridge Trus
Human Practice. Digital Ecologies. Our Future. : 14. Internationale Tagung Wirtschaftsinformatik (WI 2019) : Tagungsband
Erschienen bei: universi - Universitätsverlag Siegen. - ISBN: 978-3-96182-063-4Aus dem Inhalt:
Track 1: Produktion & Cyber-Physische Systeme
Requirements and a Meta Model for Exchanging Additive Manufacturing Capacities
Service Systems, Smart Service Systems and Cyber- Physical Systems—What’s the difference? Towards a Unified Terminology
Developing an Industrial IoT Platform – Trade-off between Horizontal and Vertical Approaches
Machine Learning und Complex Event Processing: Effiziente Echtzeitauswertung am Beispiel Smart Factory
Sensor retrofit for a coffee machine as condition monitoring and predictive maintenance use case
Stakeholder-Analyse zum Einsatz IIoT-basierter Frischeinformationen in der Lebensmittelindustrie
Towards a Framework for Predictive Maintenance Strategies in Mechanical Engineering - A Method-Oriented Literature Analysis
Development of a matching platform for the requirement-oriented selection of cyber physical systems for SMEs
Track 2: Logistic Analytics
An Empirical Study of Customers’ Behavioral Intention to Use Ridepooling Services – An Extension of the Technology Acceptance Model
Modeling Delay Propagation and Transmission in Railway Networks
What is the impact of company specific adjustments on the acceptance and diffusion of logistic standards?
Robust Route Planning in Intermodal Urban Traffic
Track 3: Unternehmensmodellierung & Informationssystemgestaltung (Enterprise Modelling & Information Systems Design)
Work System Modeling Method with Different Levels of Specificity and Rigor for Different Stakeholder Purposes
Resolving Inconsistencies in Declarative Process Models based on Culpability Measurement
Strategic Analysis in the Realm of Enterprise Modeling – On the Example of Blockchain-Based Initiatives for the Electricity Sector
Zwischenbetriebliche Integration in der Möbelbranche: Konfigurationen und Einflussfaktoren
Novices’ Quality Perceptions and the Acceptance of Process Modeling Grammars
Entwicklung einer Definition für Social Business Objects (SBO) zur Modellierung von Unternehmensinformationen
Designing a Reference Model for Digital Product Configurators
Terminology for Evolving Design Artifacts
Business Role-Object Specification: A Language for Behavior-aware Structural Modeling of Business Objects
Generating Smart Glasses-based Information Systems with BPMN4SGA: A BPMN Extension for Smart Glasses Applications
Using Blockchain in Peer-to-Peer Carsharing to Build Trust in the Sharing Economy
Testing in Big Data: An Architecture Pattern for a Development Environment for Innovative, Integrated and Robust Applications
Track 4: Lern- und Wissensmanagement (e-Learning and Knowledge Management)
eGovernment Competences revisited – A Literature Review on necessary Competences in a Digitalized Public Sector
Say Hello to Your New Automated Tutor – A Structured Literature Review on Pedagogical Conversational Agents
Teaching the Digital Transformation of Business Processes: Design of a Simulation Game for Information Systems Education
Conceptualizing Immersion for Individual Learning in Virtual Reality
Designing a Flipped Classroom Course – a Process Model
The Influence of Risk-Taking on Knowledge Exchange and Combination
Gamified Feedback durch Avatare im Mobile Learning
Alexa, Can You Help Me Solve That Problem? - Understanding the Value of Smart Personal Assistants as Tutors for Complex Problem Tasks
Track 5: Data Science & Business Analytics
Matching with Bundle Preferences: Tradeoff between Fairness and Truthfulness
Applied image recognition: guidelines for using deep learning models in practice
Yield Prognosis for the Agrarian Management of Vineyards using Deep Learning for Object Counting
Reading Between the Lines of Qualitative Data – How to Detect Hidden Structure Based on Codes
Online Auctions with Dual-Threshold Algorithms: An Experimental Study and Practical Evaluation
Design Features of Non-Financial Reward Programs for Online Reviews: Evaluation based on Google Maps Data
Topic Embeddings – A New Approach to Classify Very Short Documents Based on Predefined Topics
Leveraging Unstructured Image Data for Product Quality Improvement
Decision Support for Real Estate Investors: Improving Real Estate Valuation with 3D City Models and Points of Interest
Knowledge Discovery from CVs: A Topic Modeling Procedure
Online Product Descriptions – Boost for your Sales?
Entscheidungsunterstützung durch historienbasierte Dienstreihenfolgeplanung mit Pattern
A Semi-Automated Approach for Generating Online Review Templates
Machine Learning goes Measure Management: Leveraging Anomaly Detection and Parts Search to Improve Product-Cost Optimization
Bedeutung von Predictive Analytics für den theoretischen Erkenntnisgewinn in der IS-Forschung
Track 6: Digitale Transformation und Dienstleistungen
Heuristic Theorizing in Software Development: Deriving Design Principles for Smart Glasses-based Systems
Mirroring E-service for Brick and Mortar Retail: An Assessment and Survey
Taxonomy of Digital Platforms: A Platform Architecture Perspective
Value of Star Players in the Digital Age
Local Shopping Platforms – Harnessing Locational Advantages for the Digital Transformation of Local Retail Outlets: A Content Analysis
A Socio-Technical Approach to Manage Analytics-as-a-Service – Results of an Action Design Research Project
Characterizing Approaches to Digital Transformation: Development of a Taxonomy of Digital Units
Expectations vs. Reality – Benefits of Smart Services in the Field of Tension between Industry and Science
Innovation Networks and Digital Innovation: How Organizations Use Innovation Networks in a Digitized Environment
Characterising Social Reading Platforms— A Taxonomy-Based Approach to Structure the Field
Less Complex than Expected – What Really Drives IT Consulting Value
Modularity Canvas – A Framework for Visualizing Potentials of Service Modularity
Towards a Conceptualization of Capabilities for Innovating Business Models in the Industrial Internet of Things
A Taxonomy of Barriers to Digital Transformation
Ambidexterity in Service Innovation Research: A Systematic Literature Review
Design and success factors of an online solution for cross-pillar pension information
Track 7: IT-Management und -Strategie
A Frugal Support Structure for New Software Implementations in SMEs
How to Structure a Company-wide Adoption of Big Data Analytics
The Changing Roles of Innovation Actors and Organizational Antecedents in the Digital Age
Bewertung des Kundennutzens von Chatbots für den Einsatz im Servicedesk
Understanding the Benefits of Agile Software Development in Regulated Environments
Are Employees Following the Rules? On the Effectiveness of IT Consumerization Policies
Agile and Attached: The Impact of Agile Practices on Agile Team Members’ Affective Organisational Commitment
The Complexity Trap – Limits of IT Flexibility for Supporting Organizational Agility in Decentralized Organizations
Platform Openness: A Systematic Literature Review and Avenues for Future Research
Competence, Fashion and the Case of Blockchain
The Digital Platform Otto.de: A Case Study of Growth, Complexity, and Generativity
Track 8: eHealth & alternde Gesellschaft
Security and Privacy of Personal Health Records in Cloud Computing Environments – An Experimental Exploration of the Impact of Storage Solutions and Data Breaches
Patientenintegration durch Pfadsysteme
Digitalisierung in der Stressprävention – eine qualitative Interviewstudie zu Nutzenpotenzialen
User Dynamics in Mental Health Forums – A Sentiment Analysis Perspective
Intent and the Use of Wearables in the Workplace – A Model Development
Understanding Patient Pathways in the Context of Integrated Health Care Services - Implications from a Scoping Review
Understanding the Habitual Use of Wearable Activity Trackers
On the Fit in Fitness Apps: Studying the Interaction of Motivational Affordances and Users’ Goal Orientations in Affecting the Benefits Gained
Gamification in Health Behavior Change Support Systems - A Synthesis of Unintended Side Effects
Investigating the Influence of Information Incongruity on Trust-Relations within Trilateral Healthcare Settings
Track 9: Krisen- und Kontinuitätsmanagement
Potentiale von IKT beim Ausfall kritischer Infrastrukturen: Erwartungen, Informationsgewinnung und Mediennutzung der Zivilbevölkerung in Deutschland
Fake News Perception in Germany: A Representative Study of People’s Attitudes and Approaches to Counteract Disinformation
Analyzing the Potential of Graphical Building Information for Fire Emergency Responses: Findings from a Controlled Experiment
Track 10: Human-Computer Interaction
Towards a Taxonomy of Platforms for Conversational Agent Design
Measuring Service Encounter Satisfaction with Customer Service Chatbots using Sentiment Analysis
Self-Tracking and Gamification: Analyzing the Interplay of Motivations, Usage and Motivation Fulfillment
Erfolgsfaktoren von Augmented-Reality-Applikationen: Analyse von Nutzerrezensionen mit dem Review-Mining-Verfahren
Designing Dynamic Decision Support for Electronic Requirements Negotiations
Who is Stressed by Using ICTs? A Qualitative Comparison Analysis with the Big Five Personality Traits to Understand Technostress
Walking the Middle Path: How Medium Trade-Off Exposure Leads to Higher Consumer Satisfaction in Recommender Agents
Theory-Based Affordances of Utilitarian, Hedonic and Dual-Purposed Technologies: A Literature Review
Eliciting Customer Preferences for Shopping Companion Apps: A Service Quality Approach
The Role of Early User Participation in Discovering Software – A Case Study from the Context of Smart Glasses
The Fluidity of the Self-Concept as a Framework to Explain the Motivation to Play Video Games
Heart over Heels? An Empirical Analysis of the Relationship between Emotions and Review Helpfulness for Experience and Credence Goods
Track 11: Information Security and Information Privacy
Unfolding Concerns about Augmented Reality Technologies: A Qualitative Analysis of User Perceptions
To (Psychologically) Own Data is to Protect Data: How Psychological Ownership Determines Protective Behavior in a Work and Private Context
Understanding Data Protection Regulations from a Data Management Perspective: A Capability-Based Approach to EU-GDPR
On the Difficulties of Incentivizing Online Privacy through Transparency: A Qualitative Survey of the German Health Insurance Market
What is Your Selfie Worth? A Field Study on Individuals’ Valuation of Personal Data
Justification of Mass Surveillance: A Quantitative Study
An Exploratory Study of Risk Perception for Data Disclosure to a Network of Firms
Track 12: Umweltinformatik und nachhaltiges Wirtschaften
Kommunikationsfäden im Nadelöhr – Fachliche Prozessmodellierung der Nachhaltigkeitskommunikation am Kapitalmarkt
Potentiale und Herausforderungen der Materialflusskostenrechnung
Computing Incentives for User-Based Relocation in Carsharing
Sustainability’s Coming Home: Preliminary Design Principles for the Sustainable Smart District
Substitution of hazardous chemical substances using Deep Learning and t-SNE
A Hierarchy of DSMLs in Support of Product Life-Cycle Assessment
A Survey of Smart Energy Services for Private Households
Door-to-Door Mobility Integrators as Keystone Organizations of Smart Ecosystems: Resources and Value Co-Creation – A Literature Review
Ein Entscheidungsunterstützungssystem zur ökonomischen Bewertung von Mieterstrom auf Basis der Clusteranalyse
Discovering Blockchain for Sustainable Product-Service Systems to enhance the Circular Economy
Digitale Rückverfolgbarkeit von Lebensmitteln: Eine verbraucherinformatische Studie
Umweltbewusstsein durch audiovisuelles Content Marketing? Eine experimentelle Untersuchung zur Konsumentenbewertung nachhaltiger Smartphones
Towards Predictive Energy Management in Information Systems: A Research Proposal
A Web Browser-Based Application for Processing and Analyzing Material Flow Models using the MFCA Methodology
Track 13: Digital Work - Social, mobile, smart
On Conversational Agents in Information Systems Research: Analyzing the Past to Guide Future Work
The Potential of Augmented Reality for Improving Occupational First Aid
Prevent a Vicious Circle! The Role of Organizational IT-Capability in Attracting IT-affine Applicants
Good, Bad, or Both? Conceptualization and Measurement of Ambivalent User Attitudes Towards AI
A Case Study on Cross-Hierarchical Communication in Digital Work Environments
‘Show Me Your People Skills’ - Employing CEO Branding for Corporate Reputation Management in Social Media
A Multiorganisational Study of the Drivers and Barriers of Enterprise Collaboration Systems-Enabled Change
The More the Merrier? The Effect of Size of Core Team Subgroups on Success of Open Source Projects
The Impact of Anthropomorphic and Functional Chatbot Design Features in Enterprise Collaboration Systems on User Acceptance
Digital Feedback for Digital Work? Affordances and Constraints of a Feedback App at InsurCorp
The Effect of Marker-less Augmented Reality on Task and Learning Performance
Antecedents for Cyberloafing – A Literature Review
Internal Crowd Work as a Source of Empowerment - An Empirical Analysis of the Perception of Employees in a Crowdtesting Project
Track 14: Geschäftsmodelle und digitales Unternehmertum
Dividing the ICO Jungle: Extracting and Evaluating Design Archetypes
Capturing Value from Data: Exploring Factors Influencing Revenue Model Design for Data-Driven Services
Understanding the Role of Data for Innovating Business Models: A System Dynamics Perspective
Business Model Innovation and Stakeholder: Exploring Mechanisms and Outcomes of Value Creation and Destruction
Business Models for Internet of Things Platforms: Empirical Development of a Taxonomy and Archetypes
Revitalizing established Industrial Companies: State of the Art and Success Principles of Digital Corporate Incubators
When 1+1 is Greater than 2: Concurrence of Additional Digital and Established Business Models within Companies
Special Track 1: Student Track
Investigating Personalized Price Discrimination of Textile-, Electronics- and General Stores in German Online Retail
From Facets to a Universal Definition – An Analysis of IoT Usage in Retail
Is the Technostress Creators Inventory Still an Up-To-Date Measurement Instrument? Results of a Large-Scale Interview Study
Application of Media Synchronicity Theory to Creative Tasks in Virtual Teams Using the Example of Design Thinking
TrustyTweet: An Indicator-based Browser-Plugin to Assist Users in Dealing with Fake News on Twitter
Application of Process Mining Techniques to Support Maintenance-Related Objectives
How Voice Can Change Customer Satisfaction: A Comparative Analysis between E-Commerce and Voice Commerce
Business Process Compliance and Blockchain: How Does the Ethereum Blockchain Address Challenges of Business Process Compliance?
Improving Business Model Configuration through a Question-based Approach
The Influence of Situational Factors and Gamification on Intrinsic Motivation and Learning
Evaluation von ITSM-Tools für Integration und Management von Cloud-Diensten am Beispiel von ServiceNow
How Software Promotes the Integration of Sustainability in Business Process Management
Criteria Catalog for Industrial IoT Platforms from the Perspective of the Machine Tool Industry
Special Track 3: Demos & Prototyping
Privacy-friendly User Location Tracking with Smart Devices: The BeaT Prototype
Application-oriented robotics in nursing homes
Augmented Reality for Set-up Processe
Mixed Reality for supporting Remote-Meetings
Gamification zur Motivationssteigerung von Werkern bei der Betriebsdatenerfassung
Automatically Extracting and Analyzing Customer Needs from Twitter: A “Needmining” Prototype
GaNEsHA: Opportunities for Sustainable Transportation in Smart Cities
TUCANA: A platform for using local processing power of edge devices for building data-driven services
Demonstrator zur Beschreibung und Visualisierung einer kritischen Infrastruktur
Entwicklung einer alltagsnahen persuasiven App zur Bewegungsmotivation für ältere Nutzerinnen und Nutzer
A browser-based modeling tool for studying the learning of conceptual modeling based on a multi-modal data collection approach
Exergames & Dementia: An interactive System for People with Dementia and their Care-Network
Workshops
Workshop Ethics and Morality in Business Informatics (Workshop Ethik und Moral in der Wirtschaftsinformatik – EMoWI’19)
Model-Based Compliance in Information Systems - Foundations, Case Description and Data Set of the MobIS-Challenge for Students and Doctoral Candidates
Report of the Workshop on Concepts and Methods of Identifying Digital Potentials in Information Management
Control of Systemic Risks in Global Networks - A Grand Challenge to Information Systems Research
Die Mitarbeiter von morgen - Kompetenzen künftiger Mitarbeiter im Bereich Business Analytics
Digitaler Konsum: Herausforderungen und Chancen der Verbraucherinformati
Text mining aplicado à gestão de fundos públicos
Este trabalho tem como objetivo analisar documentos textuais submetidos por empresas
portuguesas no momento de candidatura a programas de incentivos empresariais públicos. Com
esta análise pretende-se extrair e selecionar variáveis relevantes, presentes nos textos, que
possuam poder preditivo em relação a futuras ações das empresas candidatas aceites, no
decorrer dos projetos. O objetivo concreto é a predição da anulação de projetos com fundos
atribuídos, durante a sua duração prevista. Para realizar esta análise foi necessário criar uma
cadeia de classificação de texto na qual são aplicadas variadas técnicas de processamento da
língua natural, extração e seleção de variáveis, seleção e utilização de classificadores, e métricas
de avaliação dos resultados. Foram utilizadas técnicas de referência de extração de variáveis
como a extração de valores TF e TF-IDF e foram igualmente levadas a cabo experiências de
extração de variáveis baseadas em geração de tópicos, análise de similaridade textual, análise
de diversidade lexical, exploração de vocabulário específico, entre outros tipos de análise do
conteúdo textual. A exploração de variáveis criadas a partir destas experiências mostra-nos
características escondidas nos dados, como por exemplo, o facto de se verificar uma maior
incidência de projetos com elevados níveis de similaridade em certos distritos do país. O
principal objetivo foi alcançar o melhor desempenho possível nas métricas obtidas através da
matriz de confusão (taxa de acerto; precisão; cobertura; F1-Score) na predição da anulação de
projetos. Os melhores resultados da predição de anulação foram obtidos por um conjunto de
variáveis provenientes de diversos métodos de extração e utilizando o algoritmo Classificador
Naïve Bayes: 79% de taxa de acerto; 77% de precisão; 71% de cobertura; 74% de F1-Score.
Neste trabalho é assim demonstrado o proveito da mistura de variáveis provenientes de
diferentes métodos de extração de variáveis.This work aims to analyze the textual documents presented by Portuguese companies when
applying for business incentive programs. This work intends to extract and select relevant
features, present in the texts, which have predictive power in relation to future actions of the
companies whose projects were accepted, during the projects. The concrete goal is the
prediction of the cancellation of the projects with allocated funds, during their expected
duration. It was necessary to create a text classification pipeline which applies natural language
processing, various features extraction and selection techniques, classification algorithms and
evaluation metrics. Many feature extraction techniques were used, such as classical techniques
as TF and TF-IDF values generation, as also other experiments as topic generation, similarity
analysis, lexical analysis, identification of specific vocabulary used, among other analysis of
textual content that were also carried out. The feature analysis can show us hidden
characteristics in the data, such as the fact that there is a preponderance of projects with high
levels of similarity in certain districts of the country. The main objective, regarding the perdition
of cancellation of the projects, was achieving the best possible performance, for that there were
used the confusion matrix metrics (accuracy; precision; revocation; F1-Score). The best
prediction results were obtained by a set of features from different extraction methods together
with the use of the Naïve Bayes Classifier algorithm: 79% accuracy; 77% precision; 71% recall;
74% F1-Score. Therefore, it is shown the advantages of mixing features from different
extraction methods on this text classification application
Can Upward Brand Extensions be an Opportunity for Marketing Managers During the Covid-19 Pandemic and Beyond?
Early COVID-19 research has guided current managerial practice by introducing
more products across different product categories as consumers tried to avoid
perceived health risks from food shortages, i.e. horizontal brand extensions. For
example, Leon, a fast-food restaurant in the UK, introduced a new range of ready
meal products. However, when the food supply stabilised, availability may no
longer be a concern for consumers. Instead, job losses could be a driver of higher
perceived financial risks. Meanwhile, it remains unknown whether the perceived
health or financial risks play a more significant role on consumers’ consumptions.
Our preliminary survey shows perceived health risks outperform perceived
financial risks to positively influence purchase intention during COVID-19. We
suggest such a result indicates an opportunity for marketers to consider
introducing premium priced products, i.e. upward brand extensions. The risk-as�feelings and signalling theories were used to explain consumer choice under risk may adopt affective heuristic processing, using minimal cognitive efforts to
evaluate products. Based on this, consumers are likely to be affected by the salient
high-quality and reliable product cue of upward extension signalled by its
premium price level, which may attract consumers to purchase when they have
high perceived health risks associated with COVID-19. Addressing this, a series of
experimental studies confirm that upward brand extensions (versus normal new
product introductions) can positively moderate the positive effect between
perceived health risks associated with COVID-19 and purchase intention. Such an
effect can be mediated by affective heuristic information processing. The results
contribute to emergent COVID-19 literature and managerial practice during the
pandemic but could also inform post-pandemic thinking around vertical brand
extensions
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