The present study was conducted with the purpose of determining and comparing the images of Rwanda as a tourist destination as perceived by visitors and as projected by international tour operators. The employed instruments consisted of two independent, but in their main parts, identical questionnaire surveys that featured both structured and unstructured methods in order to capture the various components of the image construct. The study identified several important differences between the perceptions of visitors and tour operators, thereby indicating that the latter project inadequate or even negative images of the country. The three main discrepancies appeared to be the evaluation of the current safety situation, opinions about the range Blazer Nike of activities offered, and views concerning the value of visitors’ encounters with the local people at the destination. The results offered valuable policy implications for future marketing strategies in Rwanda.
This Blazer Nike Leopard paper presents a novel method for contextualizing and enriching large semantic knowledge bases for opinion mining with a focus on Web intelligence platforms and other high-throughput big data applications. The method is not only applicable to traditional sentiment lexicons, but also to more comprehensive, multi-dimensional affective resources such as SenticNet. It comprises the following steps: (i) identify ambiguous sentiment terms, (ii) provide context information extracted from a domain-specific training corpus, and (iii) ground this contextual information to structured background knowledge sources such as ConceptNet and WordNet. A quantitative evaluation shows a significant improvement when using an enriched version of SenticNet for polarity classification. Crowdsourced gold standard data in conjunction with a qualitative evaluation sheds light on the Chaussure Nike Blazer strengths and weaknesses of the concept grounding, and on the quality of the enrichment process.
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