Ramona Paun

Twitter Ontology-Driven Sentiment Analysis

As the usage of micro-blogging services has rapidly increased in the last few years, services such as Twitter have become a rich source of opinion information, highly useful for better understanding peoples’ feelings and emotions. Making sense of this huge amount of data, would provide invaluable benefits to companies, organizations and governments alike, by better understanding what the public thinks about their services and products. However, almost all existing approaches used for social networks sentiment analysis are only able to determine whether the message has a positive, negative or neutral connotation, without any information regarding the actual emotions. Besides, critical information is lost, as the determined perception is only associated with the entire tweet and not with the distinct notions present in the message. For this reason, the present paper proposes a novel semantic social media analysis approach, TweetOntoSense, which uses ontologies to model complex feeling such as happiness, affection, surprise, anger or sadness. By storing the results as structured data, the possibilities offered by the semantic web technologies can be fully exploited.

Understanding Online Social Networks’ Users – A Twitter Approach

Twitter messages, also known as tweets, are increasingly used by marketers worldwide to determine consumer sentiments towards brands, products or events. Currently, most existing approaches used for social networks sentiment analysis only extract simple feedbacks in terms of positive and negative perception. In this paper, TweetOntoSense is proposed - a semantic based approach that uses ontologies in order to infer the actual user’s emotions. The extracted sentiments are described using a WordNet enriched emotional categories ontology. Thus, feelings such as happiness, affection, surprise, anger, sadness, etc. are put forth. Moreover, compared to existing approaches, TweetOntoSense also takes into consideration the fact that a single tweet message might express several, rather than a single emotion. A case study on Twitter is performed, also showing this approach’s practical applicability.

Grey Social Networks

Facebook is one of the largest socializing networks nowadays, gathering among his users a whole array of persons from all over the world, with a diversified background, culture, opinions, age and so on. Here is the meeting point for friends (both real and virtual), acquaintances, colleagues, team-mates, class-mates, co-workers, etc. Also, here is the land where the information is spreading so fast and where you can easily exchange your opinions, feelings, traveling informations, ideas, etc. But what happens when one is reading the news feed or is seeing his Facebook friends’ photos? Is he thrilled, excited? Is he feeling that the life is good? Or contrary: he is feeling lonely, isolated? Is he doing a comparison with his friends? These are some of the questions this paper in trying to answer and shaping some of these relationships, the grey system theory will be used.

A Healthcare Companies’ Performance View through OSN

In the new economic context, the on-line social networks (OSN) are gathering among their users a whole array of persons, with a diversified background, culture, opinions and needs. Here is the meeting point for persons looking for information on different domains and areas of interest and also here is the exchange land for thoughts, experiences, news, etc. As the companies have sensed the global phenomenon of the OSN, they have paid more attention to the on-line social environment, investing more in the social media campaigns. But what about the companies in the healthcare system? Are their customers seeking for information in OSN? And if so, to what extent the information provided here is useful? Namely, is the OSN affecting their performance?

How Impressionable Are You? - Grey Knowledge, Groups and Strategies in OSN

Today’s leading businesses have understood the role of “social” into their everyday activity. Online social networks (OSN) and social media have melt and become an essential part of every firm’s concerns. Brand advocates are the new leading triggers for company’s success in online social networks and are responsible for the long term engagement between a firm and its customers. But what can it be said about this impressive crowd of customers that are gravitating around a certain brand advocacy or a certain community? Are they as responsive to a certain message as one might think? Are they really impressed by the advertising campaigns? Are they equally reacting to a certain comment or news? How they process the everyday grey knowledge that is circulating in OSN? In fact, how impressionable they are and which are the best ways a company can get to them?

Agent-Based Optimization of the Emergency Exits and Desks Placement in Classrooms

Even though the average number of structure fires in educational properties have fallen by 67% since 1980, the National Fire Protection Association has still recorded an average of 4980 structure fires (2011–2015), causing annual damages of 1 death, 70 injuries and

Are You Really Influencing Your Customers?: A Black-Friday Analysis

70 million in direct property damage. A series of studies have been conducted over the time in order to minimize the loses, with a particular focus on saving humans life. Thus, in order to reduce the evacuation time and the causalities, factors such as: the distance to exit, the density around the exit, room information, the presence of individuals with disabilities, heterogeneous population and obstacles have been considered. In this context, the present paper aims to determine if there is any connection between the structure of the classroom in terms of placing the exits and the desk placement. For this, a simulation is made using heterogeneous agents and a classroom with two exits. As the position of the exits is rather less changeable in real life as it depends directly on the building’s characteristics, the desk placement can be easily modified inside the classroom with effects on the evacuation time.

Healthcare Risk Management Analysis - A Bibliometric Approach

The concept of Black Friday appeared more than 50 years ago and is known as an American holiday retail and in time it has crossed the borders of US and was been widely adopted by other countries from all over the world. For this, the present paper aims to analyze some qualitative aspects related to the consumers’ behavior and the Black Friday promotions, such as: what are the most purchased products, what are the most preferred brands, to whom are bought these products, what is the average budget, what is the allocated time, the post-sale consumer satisfaction, etc. Moreover, the paper uses a questionnaire for determining the impact that Black Friday has on the consumers’ future opinion over the different brands and how the companies’ advertisements and campaigns on online social net-works can change the consumers’ behavior in this day. In addition, the grey systems theory, a newly developed theory in the field of artificial intelligence, was used in order to shape the relationship among the considered variables which are influencing the consumers’ behavior on Black Friday.

Grey Social Networks - A Facebook Case Study.

Using a large-scale dataset from WoS, this paper explores the publications on healthcare risk management, through bibliometric analysis. The bibliometric analysis reflects how research in hospital risk management and healthcare management evolved over time, offering insights on the most relevant and influential research. Based on the idea that researchers publish their most important results in articles, conferences, books and reviews, there is diffusion in this research field, with many reference countries. The bibliometric analysis reflects the growing interest of research for the area of healthcare risk management. The need to provide high quality medical services requires the design and implementation of a set of key performance indicators for each strategic objective set by the hospital management.