Social analytics: Learning fuzzy product ontologies for aspect-oriented sentiment analysis

A survey on opinion mining and sentiment analysis: Tasks, approaches and applications

“…Lau et al [182] enacted an ontology learning system for contextual aspect-level SA. They generated ontology in two phases: in the first phase implicit and explicit aspects ontology was generated.…”

“…The paper is concluded in section 5. Document level 73 [13], [18], [22], [32], [33], [36], [40], [43], [45], [48], [50], [51], [53], [54], [61], [64], [66], [77], [81], [80], [85], [88], [90], [91], [94], [96], [101], [111], [117], [121], [123], [130], [131], [132], [148], [155], [156], [157], [158], [167], [168], [169], [175], [176], [177], [179], [180], [182], [194], [195], …”

EXPRS: An extended pagerank method for product feature extraction from online consumer reviews

“…First, the explosive growth of online product reviews makes it time-consuming and ineffective for a consumer to navigate individual reviews one by one in order to obtain useful information about a product, causing an information overload problem [25]. Previous studies have shown that information overload negatively influences purchase decisions considerably and may lead to fewer consumer purchases [5,8,15].…”

Las Ontologías para la detección automática de aspectos en el Análisis de Sentimientos

“…El nivel de frase clasifica el sentimiento expresado en cada oración y el de aspectos lo clasifica con respecto a las características específicas de una entidad encontradas en cada frase. Los dos primeros enfoques, resultan a veces incompletos ante la realidad de las empresas u organizaciones que quieren saber en detalle el comportamiento de su producto [5]. Este tipo de análisis no permite a las organizaciones tener la seguridad o la entereza de tomar algunas acciones correctivas o incluso la toma de decisiones estratégicas.…”