3 research outputs found
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