How Consumers’ Styles of Thinking Can Control Brand Dilution

2018 ◽  
Vol 10 (1) ◽  
pp. 40-45 ◽  
Author(s):  
Alokparna Basu Monga ◽  
Liwu Hsu
Keyword(s):  
Crisis Management ◽  
State Of The Art ◽  
Contextual Factors ◽  
Negative Information ◽  
Negative Events ◽  
Crisis Communications ◽  
Negative Thoughts ◽  
Brand Dilution ◽  
Manufacturing Problems ◽  
Powerful Mechanism

Abstract Understanding consumers’ ways of thinking can help identify strategies to limit brand damage and elicit more favorable reactions from disapproving consumers. Analytic thinkers’ beliefs about a brand are diluted when they see negative information; those of holistic thinkers remain unaffected. While both analytic and holistic thinkers blame the brand equally for quality and manufacturing problems, holistic thinkers are more likely to blame contextual factors outside of the brand than analytic thinkers. This ability of holistic thinkers to focus on the outside context is the reason why their brand beliefs are not diluted. State-of-the-art crisis management should be proactive vis-à-vis potentially negative events. Crisis communications that highlight contextual factors as triggers of negative incidents offer a powerful mechanism to restrict brand damage. Additionally, elaborational messages that clarify the nature of the brand extension can curb negative thoughts from analytic consumers and boost their responses.

Enhanced context-aware recommendation using topic modeling and particle swarm optimization

2021 ◽  
pp. 1-16
Author(s):  
Ibtissem Gasmi ◽  
Mohamed Walid Azizi ◽  
Hassina Seridi-Bouchelaghem ◽  
Nabiha Azizi ◽  
Samir Brahim Belhaouari
Keyword(s):  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
State Of The Art ◽  
Weighting Function ◽  
Contextual Factors ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Pso Algorithm ◽  
Context Aware ◽  
Proposed Model

Context-Aware Recommender System (CARS) suggests more relevant services by adapting them to the user’s specific context situation. Nevertheless, the use of many contextual factors can increase data sparsity while few context parameters fail to introduce the contextual effects in recommendations. Moreover, several CARSs are based on similarity algorithms, such as cosine and Pearson correlation coefficients. These methods are not very effective in the sparse datasets. This paper presents a context-aware model to integrate contextual factors into prediction process when there are insufficient co-rated items. The proposed algorithm uses Latent Dirichlet Allocation (LDA) to learn the latent interests of users from the textual descriptions of items. Then, it integrates both the explicit contextual factors and their degree of importance in the prediction process by introducing a weighting function. Indeed, the PSO algorithm is employed to learn and optimize weights of these features. The results on the Movielens 1 M dataset show that the proposed model can achieve an F-measure of 45.51% with precision as 68.64%. Furthermore, the enhancement in MAE and RMSE can respectively reach 41.63% and 39.69% compared with the state-of-the-art techniques.

scholarly journals Integrative Approach to Internal and External Crisis  Communications Management. Part 2

2019 ◽  
Vol 9 (2) ◽  
pp. 23-33
Author(s):  
T.  I. Alifanova
Keyword(s):  
Crisis Management ◽  
Organizational Management ◽  
Time Frame ◽  
Integrative Approach ◽  
Extensive Literature ◽  
Main Attention ◽  
Crisis Communications ◽  
Crisis Prevention ◽  
Extensive List ◽  
Structural Aspects

As noted in the first part of the paper in the extensive literature on crises and crisis management, it is possible to allocate two main directions: internal —  where the main attention is paid to technical and structural aspects and external — where the organization focuses on managing of stakeholders. Despite the fact that over past 20 years each of these directions has being developed to a large extent independently, it had been revealed that there were definite number of opportunities for their integration. Based on the results of research given in the extensive list of used literature, it will be shown how both of these perspectives can be combined into single integrated structure. At the same time the study of potential for synthesis of internal and external perspectives is going to be covered by time frame of three main crisis stages: pre-crisis prevention, crisis management and post-crisis outcomes, and term “crisis management” will reflect activities at these stages of organizational management in broadest sense.

An Approach to Distinguish Between the Severity of Bullying in Messages in Social Media

2016 ◽  
Vol 3 (4) ◽  
pp. 1-20 ◽  
Author(s):  
Geetika Sarna ◽  
M.P.S. Bhatia
Keyword(s):  
Social Media ◽  
Preventive Measures ◽  
State Of The Art ◽  
Negative Information ◽  
Security And Privacy ◽  
Multimedia Content ◽  
The Real ◽  
The Social

Users on the social media can share positive as well as negative information intentionally and unintentionally in the form of multimedia content without knowing its impact on other user, which threatens the security and privacy of social media. Cyberbullying is one of the risks associated with social media. Cyberbullying is an aggressive act carried out intentionally against the victim by posting harmful material on social media to harm his/her reputation. Aggressive act creates depression, anxiety in users which may lead to diversion of attention and sometimes suicidal actions. In this paper the authors have included a survey on recent algorithms which work on detection of cyberbullying. State-of-the-art studies only focus on the detection of cyberbullying but not on the preventive measures against cyberbullying. In order to tackle this problem, the authors showed how the severity of the bullying in messages helps to find the real culprit.

scholarly journals In Human Memory, Good Can Be Stronger Than Bad

2020 ◽  
Vol 29 (1) ◽  
pp. 86-91 ◽  
Author(s):  
Constantine Sedikides ◽  
John J. Skowronski
Keyword(s):  
False Memory ◽  
Psychological Impact ◽  
Human Memory ◽  
Negative Information ◽  
Negative Events ◽  
Regulatory Activity ◽  
Positive Information ◽  
Positive Events ◽  
Self Protection ◽  
Positive Content

Some researchers assert that the psychological impact of negative information is more powerful than that of positive information. This assertion is qualified in the domain of human memory, in which (a) positive content is often favored (in the strength of memories for real stimuli or events and in false-memory generation) over negative content and (b) the affect prompted by memories of positive events is more temporally persistent than the affect prompted by memories of negative events. We suggest that both of these phenomena reflect the actions of self-motives (i.e., self-protection and self-enhancement), which instigate self-regulatory activity and self-relevant processes.

An Effective Recommender System Based on Clustering Technique for TED Talks

2020 ◽  
Vol 15 (1) ◽  
pp. 35-51 ◽  
Author(s):  
Faiz Maazouzi ◽  
Hafed Zarzour ◽  
Yaser Jararweh
Keyword(s):  
Collaborative Filtering ◽  
Recommender Systems ◽  
Recommender System ◽  
Information Overload ◽  
State Of The Art ◽  
Pearson Correlation ◽  
Enormous Amount ◽  
Powerful Mechanism ◽  
Ted Talks

With the enormous amount of information circulating on the Web, it is becoming increasingly difficult to find the necessary and useful information quickly and efficiently. However, with the emergence of recommender systems in the 1990s, reducing information overload became easy. In the last few years, many recommender systems employ the collaborative filtering technology, which has been proven to be one of the most successful techniques in recommender systems. Nowadays, the latest generation of collaborative filtering methods still requires further improvements to make the recommendations more efficient and accurate. Therefore, the objective of this article is to propose a new effective recommender system for TED talks that first groups users according to their preferences, and then provides a powerful mechanism to improve the quality of recommendations for users. In this context, the authors used the Pearson Correlation Coefficient (PCC) method and TED talks to create the TED user-user matrix. Then, they used the k-means clustering method to group the same users in clusters and create a predictive model. Finally, they used this model to make relevant recommendations to other users. The experimental results on real dataset show that their approach significantly outperforms the state-of-the-art methods in terms of RMSE, precision, recall, and F1 scores.

scholarly journals A Taxonomy of Crisis Management Functions

2020 ◽  
Vol 12 (12) ◽  
pp. 5147
Author(s):  
Todor Tagarev ◽  
Valeri Ratchev
Keyword(s):  
Crisis Management ◽  
Lessons Learned ◽  
The European Union ◽  
Crisis Communications ◽  
Research And Innovation ◽  
Technological Advances ◽  
Innovation Project ◽  
Risk Reduction Measures ◽  
Search For Information ◽  
Management Functions

The management of crises triggered by natural or manmade events requires a concerted effort of various actors crossing institutional and geographic boundaries. Technological advances allow to make crisis management more effective, but innovation is hindered by dispersed and often disconnected knowledge on the lessons learned, gaps, and solutions. Taxonomies enable the search for information of potential interest. This article presents a taxonomy of crisis management functions, designed on the basis of a conceptual model integrating the concepts of hazard, vulnerability, risk, and community, and the main consequence- and management-based concepts. At its highest level, the taxonomy includes ten functional areas: preparatory (mitigation, capability development, and strategic adaptiveness), operational (protection, response, and recovery), and common (crisis communications and information management; command, control, and coordination; logistics; and security management). The taxonomy facilitates the navigation of online platforms and the matching of needs and solutions. It has broader applications, e.g., for structuring the assessment of the societal impact of crisis management solutions and as a framework for a comprehensive assessment of disaster risk reduction measures. While the taxonomy was developed within a research and innovation project supported by the European Union, it reflects and is compatible with established international concepts and classification schemes, and is thus applicable by a wider international community.

An Approach to Distinguish Between the Severity of Bullying in Messages in Social Media

2016 ◽  
pp. 160-181
Author(s):  
Geetika Sarna ◽  
M.P.S. Bhatia
Keyword(s):  
Social Media ◽  
Preventive Measures ◽  
State Of The Art ◽  
Negative Information ◽  
Security And Privacy ◽  
Multimedia Content ◽  
The Real ◽  
The Social

Users on the social media can share positive as well as negative information intentionally and unintentionally in the form of multimedia content without knowing its impact on other user, which threatens the security and privacy of social media. Cyberbullying is one of the risks associated with social media. Cyberbullying is an aggressive act carried out intentionally against the victim by posting harmful material on social media to harm his/her reputation. Aggressive act creates depression, anxiety in users which may lead to diversion of attention and sometimes suicidal actions. In this paper the authors have included a survey on recent algorithms which work on detection of cyberbullying. State-of-the-art studies only focus on the detection of cyberbullying but not on the preventive measures against cyberbullying. In order to tackle this problem, the authors showed how the severity of the bullying in messages helps to find the real culprit.

scholarly journals Towards a Grid for Characterizing and Evaluating Crisis Management Serious Games

2017 ◽  
Vol 9 (3) ◽  
pp. 76-95
Author(s):  
Ibtissem Daoudi ◽  
Raoudha Chebil ◽  
Erwan Tranvouez ◽  
Wided Lejouad Chaari ◽  
Bernard Espinasse
Keyword(s):  
Crisis Management ◽  
Serious Games ◽  
State Of The Art ◽  
Assessment And Evaluation ◽  
Or Management ◽  
Analysis And Evaluation ◽  
Safe Environment ◽  
Training Costs ◽  
Evaluation Approaches ◽  
Evaluation Techniques

Over the last few decades, interest has grown in the use of serious games (SG) and their assessment in almost every sector. A privileged application domain of SG is crisis management (CM) in which these tools improve crisis behavior and/or management in a safe environment while reducing training costs. However, it is difficult to characterize and evaluate such specific SG. This article proposes a comprehensive grid defining features for description, analysis and evaluation of Crisis Management Serious Games (CMSG). First of all, the authors introduce SG, CM as well as evaluation and assessment concepts, and discuss their particular challenges by highlighting the need of using assessment and evaluation techniques to support learning and/or training. Then, the authors present, classify and compare the most relevant techniques dedicated to address this need by encompassing the state of the art of learners' assessment and evaluation approaches used in CMSG. Finally, this article presents in detail the proposed grid and discusses the major findings and contributions.

scholarly journals DisKnow: A Social-Driven Disaster Support Knowledge Extraction System

2020 ◽  
Vol 10 (17) ◽  
pp. 6083
Author(s):  
João Boné ◽  
Mariana Dias ◽  
João C. Ferreira ◽  
Ricardo Ribeiro
Keyword(s):  
Neural Networks ◽  
Crisis Management ◽  
Language Processing ◽  
Visual Information ◽  
State Of The Art ◽  
Text Processing ◽  
Data Extraction ◽  
Extraction System ◽  
Management Process ◽  
Knowledge Graphs

This research is aimed at creating and presenting DisKnow, a data extraction system with the capability of filtering and abstracting tweets, to improve community resilience and decision-making in disaster scenarios. Nowadays most people act as human sensors, exposing detailed information regarding occurring disasters, in social media. Through a pipeline of natural language processing (NLP) tools for text processing, convolutional neural networks (CNNs) for classifying and extracting disasters, and knowledge graphs (KG) for presenting connected insights, it is possible to generate real-time visual information about such disasters and affected stakeholders, to better the crisis management process, by disseminating such information to both relevant authorities and population alike. DisKnow has proved to be on par with the state-of-the-art Disaster Extraction systems, and it contributes with a way to easily manage and present such happenings.

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