Liviu-Adrian Cotfas

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.

Companies' quality characteristics vs their performance

Purpose – This paper attempts to identify the strength of the relation between the quality characteristics of companies that are activating in an economy and their performance.Design/methodology/approach – In the quality characteristics sphere were included almost all the elements related to companys behaviour on a market, in an uncertain environment and in the relations developed with stockholders. And what theory can better shape this relation than grey systems theory, a theory of uncertainty and of continual changes? At first, all of these qualitative characteristics that are reflecting companys activity have been divided into six categories for a better reality reflection. A performance indicator was also depicted by taking into consideration each companys managerial objectives.Findings – By applying grey relational analysis (GRA) in a case of eight Romanian firms, the results were convincing: not only that these characteristics determine firms evolution, but, by knowing them and acting properly o...

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.

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

GM(1, 1) in bankruptcy forecasting

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.