Box Office Forecasting considering Competitive Environment and Word-of-Mouth in Social Networks: A Case Study of Korean Film Market

Accurate box office forecasting models are developed by considering competition and word-of-mouth (WOM) effects in addition to screening-related information. Nationality, genre, ratings, and distributors of motion pictures running concurrently with the target motion picture are used to describe the competition, whereas the numbers of informative, positive, and negative mentions posted on social network services (SNS) are used to gauge the atmosphere spread by WOM. Among these candidate variables, only significant variables are selected by genetic algorithm (GA), based on which machine learning algorithms are trained to build forecasting models. The forecasts are combined to improve forecasting performance. Experimental results on the Korean film market show that the forecasting accuracy in early screening periods can be significantly improved by considering competition. In addition, WOM has a stronger influence on total box office forecasting. Considering both competition and WOM improves forecasting performance to a larger extent than when only one of them is considered

Direct Growth Of Amorphous Silica Nanowires By Solid State Transformation Of Sio2 Films

Amorphous silica nanowires (a-SiONWs) were produced by direct solid state transformation from silica films. The silica nanowires grow on TiN/Ni/SiO 2/Si substrates during the annealing in H2 or a H 2:CH4 mixture at 1050°C. Titanium nitride (TiN) films were used to induce a solid state reaction with silica (SiO2) films on silicon wafers to provide silicon atoms into growing nanowires. The TiN layers induce the diffusion of silicon and oxygen to the surface by a stress gradient built inside the films. The nickel diffuses to the surface during the TiN deposition and acts as a nucleation site for the a-SiONWs. © 2003 Elsevier B.V. All rights reserved