A Model to Measure the Spread Power of Rumors

Nowadays, a significant portion of daily interacted posts in social media are infected by rumors. This study investigates the problem of rumor analysis in different areas from other researches. It tackles the unaddressed problem related to calculating the Spread Power of Rumor (SPR) for the first time and seeks to examine the spread power as the function of multi-contextual features. For this purpose, the theory of Allport and Postman will be adopted. In which it claims that there are two key factors determinant to the spread power of rumors, namely importance and ambiguity. The proposed Rumor Spread Power Measurement Model (RSPMM) computes SPR by utilizing a textual-based approach, which entails contextual features to compute the spread power of the rumors in two categories: False Rumor (FR) and True Rumor (TR). Totally 51 contextual features are introduced to measure SPR and their impact on classification are investigated, then 42 features in two categories "importance" (28 features) and "ambiguity" (14 features) are selected to compute SPR. The proposed RSPMM is verified on two labelled datasets, which are collected from Twitter and Telegram. The results show that (i) the proposed new features are effective and efficient to discriminate between FRs and TRs. (ii) the proposed RSPMM approach focused only on contextual features while existing techniques are based on Structure and Content features, but RSPMM achieves considerably outstanding results (F-measure=83%). (iii) The result of T-Test shows that SPR criteria can significantly distinguish between FR and TR, besides it can be useful as a new method to verify the trueness of rumors

Automatic Personality Prediction; an Enhanced Method Using Ensemble Modeling

Human personality is significantly represented by those words which he/she uses in his/her speech or writing. As a consequence of spreading the information infrastructures (specifically the Internet and social media), human communications have reformed notably from face to face communication. Generally, Automatic Personality Prediction (or Perception) (APP) is the automated forecasting of the personality on different types of human generated/exchanged contents (like text, speech, image, video, etc.). The major objective of this study is to enhance the accuracy of APP from the text. To this end, we suggest five new APP methods including term frequency vector-based, ontology-based, enriched ontology-based, latent semantic analysis (LSA)-based, and deep learning-based (BiLSTM) methods. These methods as the base ones, contribute to each other to enhance the APP accuracy through ensemble modeling (stacking) based on a hierarchical attention network (HAN) as the meta-model. The results show that ensemble modeling enhances the accuracy of APP

Salting-out Effect of Ionic Liquid, 1‑Butyl-3-methyl Imidazolium Chloride on Aqueous d‑Fructose or Sucrose Solutions at <i>T</i> = 298.15 K: Vapor–Liquid Equilibrium Study

Water activity and vapor pressure for aqueous {ionic liquid, 1-butyl-3-methyl imidazolium chloride + sucrose or d-fructose} solutions have been determined using the improved isopiestic method at <i>T</i> = 298.15 K. The reliability of local composition models of NRTL, NRF-NRTL, modified NRTL, Wilson, and UNIQUAC in the fitting the water activity values for the studied systems has been examined. For saccharides in aqueous and aqueous ionic liquid solutions and for ionic liquid in aqueous solutions, the unsymmetrical molal activity coefficients were computed. The interactions present in these systems were interpreted by the comparison of the molal activity coefficients of these saccharides in aqueous and aqueous ionic liquid solutions. Furthermore, salt effect of ionic liquid, 1-butyl-3-methyl imidazolium chloride has been compared with two previously studied ionic liquids 1-butyl-3-methyl imidazolium bromide and 1-hexyl-3-methyl imidazolium chloride. In this study, the effects of chain length and anion type of ionic liquids on interactions present in these systems were also investigated