Effects of word-of-mouth communication on purchasing decisions in restaurants: A path analytic study

This study investigated the restaurant word-of-mouth communication structure. Main constructs of the word-of-mouth process on purchasing decisions were identified and their relationships were examined in a restaurant setting. Consequently, a restaurant word-of-mouth model was proposed; The main interests of study are as follows: first, to identify the main factors of restaurant word-of-mouth communication; second, to discover which word-of-mouth factors directly affect the consumer\u27s restaurant product/service purchase decision; and third, to find out the degree to which word-of-mouth factors determine the consumer\u27s word-of-mouth search efforts for a restaurant. The study also looked at the mediating effect of word-of-mouth search efforts on the purchase decision. In the end, the proposed word-of-mouth model was compared to a general-services word-of-mouth model to determine which model better explains the restaurant word-of-mouth communication structure; As the result of an extensive literature review, eight restaurant word-of-mouth constructs and fourteen hypotheses were formulated. They were based on the theoretical background of communication models, on Bansal and Voyer\u27s word-of-mouth model, and on the Theory of Planned Behavior. The data were collected via a web-based survey. The Structural Equation Modeling method was adopted to test hypotheses and eventually to answer research questions. The findings of this study suggest that factors of word-of-mouth sender\u27s expertise, reference group, and word-of-mouth search effort influence the consumer\u27s restaurant service/product purchase decision. For example, if the sender seems experienced, and if the receiver cares about how others see him when he makes an additional word-of-mouth search effort, then the influence of the sender\u27s word-of-mouth on the receiver\u27s purchase decision increases. Similarly, the perceived word-of-mouth receiver\u27s expertise, perceived risk, and self-restaurant image congruence constructs turned out to be influential factors for the consumer\u27s word-of-mouth search effort. It seems that the more educated (experienced) customers actively search word-of-mouth information when they feel more risk about the restaurant choice and when they see more of image congruence between the restaurant and themselves; It was interesting that most of the experiences reported in this study involved positive word-of-mouth. It seems that positive word-of-mouth has a bigger impact on a restaurant consumer\u27s word-of-mouth experience. It is also noteworthy that the word-of-mouth channel most respondents used was face-to-face

exBAKE: Automatic Fake News Detection Model Based on Bidirectional Encoder Representations from Transformers (BERT)

News currently spreads rapidly through the internet. Because fake news stories are designed to attract readers, they tend to spread faster. For most readers, detecting fake news can be challenging and such readers usually end up believing that the fake news story is fact. Because fake news can be socially problematic, a model that automatically detects such fake news is required. In this paper, we focus on data-driven automatic fake news detection methods. We first apply the Bidirectional Encoder Representations from Transformers model (BERT) model to detect fake news by analyzing the relationship between the headline and the body text of news. To further improve performance, additional news data are gathered and used to pre-train this model. We determine that the deep-contextualizing nature of BERT is best suited for this task and improves the 0.14 F-score over older state-of-the-art models

Call for Customized Conversation: Customized Conversation Grounding Persona and Knowledge

Humans usually have conversations by making use of prior knowledge about a topic and background information of the people whom they are talking to. However, existing conversational agents and datasets do not consider such comprehensive information, and thus they have a limitation in generating the utterances where the knowledge and persona are fused properly. To address this issue, we introduce a call For Customized conversation (FoCus) dataset where the customized answers are built with the user's persona and Wikipedia knowledge. To evaluate the abilities to make informative and customized utterances of pre-trained language models, we utilize BART and GPT-2 as well as transformer-based models. We assess their generation abilities with automatic scores and conduct human evaluations for qualitative results. We examine whether the model reflects adequate persona and knowledge with our proposed two sub-tasks, persona grounding (PG) and knowledge grounding (KG). Moreover, we show that the utterances of our data are constructed with the proper knowledge and persona through grounding quality assessment

Extremely Stable Luminescent Crosslinked Perovskite Nanoparticles under Harsh Environments over 1.5 Years

© 2020 Wiley-VCH GmbHOrganic–inorganic hybrid perovskite nanoparticles (NPs) are a very strong candidate emitter that can meet the high luminescence efficiency and high color standard of Rec.2020. However, the instability of perovskite NPs is the most critical unsolved problem that limits their practical application. Here, an extremely stable crosslinked perovskite NP (CPN) is reported that maintains high photoluminescence quantum yield for 1.5 years (>600 d) in air and in harsher liquid environments (e.g., in water, acid, or base solutions, and in various polar solvents), and for more than 100 d under 85 °C and 85% relative humidity without additional encapsulation. Unsaturated hydrocarbons in both the acid and base ligands of NPs are chemically crosslinked with a methacrylate-functionalized matrix, which prevents decomposition of the perovskite crystals. Counterintuitively, water vapor permeating through the crosslinked matrix chemically passivates surface defects in the NPs and reduces nonradiative recombination. Green-emitting and white-emitting flexible large-area displays are demonstrated, which are stable for >400 d in air and in water. The high stability of the CPN in water enables biocompatible cell proliferation which is usually impossible when toxic Pb elements are present. The stable materials design strategies provide a breakthrough toward commercialization of perovskite NPs in displays and bio-related applications.