Hogeschool Gent

About: Hogeschool Gent is a education organization based out in Ghent, Belgium. It is known for research contribution in the topics: Population & Poison control. The organization has 706 authors who have published 1453 publications receiving 41875 citations. The organization is also known as: HOGENT.

Sustainable Food Consumption: Exploring the Consumer “Attitude – Behavioral Intention” Gap

Abstract: Although public interest in sustainability increases and consumer attitudes are mainly positive, behavioral patterns are not univocally consistent with attitudes. This study investigates the presumed gap between favorable attitude towards sustainable behavior and behavioral intention to purchase sustainable food products. The impact of involvement, perceived availability, certainty, perceived consumer effectiveness (PCE), values, and social norms on consumers’ attitudes and intentions towards sustainable food products is analyzed. The empirical research builds on a survey with a sample of 456 young consumers, using a questionnaire and an experimental design with manipulation of key constructs through showing advertisements for sustainable dairy. Involvement with sustainability, certainty, and PCE have a significant positive impact on attitude towards buying sustainable dairy products, which in turn correlates strongly with intention to buy. Low perceived availability of sustainable products explains why intentions to buy remain low, although attitudes might be positive. On the reverse side, experiencing social pressure from peers (social norm) explains intentions to buy, despite rather negative personal attitudes. This study shows that more sustainable and ethical food consumption can be stimulated through raising involvement, PCE, certainty, social norms, and perceived availability.

SemEval-2016 task 5 : aspect based sentiment analysis

Abstract: This paper describes the SemEval 2016 shared task on Aspect Based Sentiment Analysis (ABSA), a continuation of the respective tasks of 2014 and 2015. In its third year, the task provided 19 training and 20 testing datasets for 8 languages and 7 domains, as well as a common evaluation procedure. From these datasets, 25 were for sentence-level and 14 for text-level ABSA; the latter was introduced for the first time as a subtask in SemEval. The task attracted 245 submissions from 29 teams.