No abstract

The growing prominence of online hate speech is a threat to a safe and just society. This endangering phenomenon requires collaboration across the sciences in order to generate evidence-based knowledge of, and policies for, the dissemination of hatred in online spaces. To foster such collaborations, here we present the Gab Hate Corpus (GHC), consisting of 27,665 posts from the social network service gab.ai, each annotated by a minimum of three trained annotators. Annotators were trained to label posts according to a coding typology derived from a synthesis of hate speech definitions across legal, computational, psychological, and sociological research. We detail the development of the corpus, describe the resulting distributions of hate-based rhetoric, target group, and rhetorical framing labels, and establish baseline classification performance for each using standard natural language processing methods. The GHC, which is the largest theoretically-justified, annotated corpus of hate speech to date, provides opportunities for training and evaluating hate speech classifiers and for scientific inquiries into the linguistic and network components of hate speech.

A lot of fuzzy models have been planned and researched to review the information under uncertainty and ambiguity. Among these, the model of the interval-valued picture fuzzy set (IVPFS) is very important which can explain the information by four possibilities in the opinion of experts using a membership degree (MD), non-membership degree (NMD), abstinence degree (AD), and a refusal degree (RD) in the form of intervals. The gathering of data is difficult all the time, particularly when the difference of opinions is connected. This article aims to explore the idea of a Maclaurin symmetric mean (MSM) operator in the framework of IVPFS. In this article, we have studied MSM in the framework of IVPFSs and discussed their application in picking the most suitable company benefit plan (CBP) using interval-valued picture fuzzy (IVPF) data. The proposed operators IVPF MSM (IVPFMSM), IVPF weighted MSM (IVPFWMSM), IVPF dual MSM (IVPFDMSM), and IVPF dual weighted MSM (IVPFDWMSM) operators are found trustworthy with the basic properties. Finally, to show the proposed method's importance and significance, a numerical example has been provided and results have been compared with some existing operators.

In this study, foliar anatomy and pollen morphology of 10 species of Acanthaceae has been investigated using light and scanning electron microscopy. The study was aimed to highlight the role of microscopy in microteaching at community for proper characterization of plants using palyno‐anatomical characters including pollen type, exine sculpturing, shape of epidermal cells, pattern of anticlinal wall, type and size of stomata, and trichome. Most of the species have polygonal cell shapes but some species have irregular, tetragonal, and pentagonal shape of epidermal cells. The largest epidermal cell length on adaxial and abaxial surface were observed in Asystasia gangetica 66.95 and 87.40 μm whereas least was observed on adaxial surface in Justicia adhatoda 36.9 μm and on abaxial surface in Barleria cristata 35.65 μm. In anatomy, species have diacytic type of stomata, whereas stomata of paracytic type observed in two species, while in A. gangetica cyclocytic type of stomata are present. Quantitively on abaxial surface, largest stomata length 29.9 μm and width 24.30 μm was noted in B. cristata. While shortest stomata length was observed in Ruellia prostrata 25.95 μm whereas minimum width of stomata was examined in Barleria acanthoides 2.05 μm. The diversity of trichomes are present in all species except in Ruellia brittoniana. Acanthaceae can be characterized by exhibiting different pollen morphology having five types of pollen shapes, prolate, spheroidal, perprolate, subprolate, and oblate spheroidal. Exine peculiarities showing variations such as reticulate, granulate, coarsely reticulate, lophoreticulate, perforate tectate, and granulate surface were examined.

Aczel-Alsina t-norm (TN) and t-conorm (TCN) were proposed by Aczel and Alsina in 1982 where they are more flexible than the other TN and TCN. Since Aczel-Alsina TN and TCN have a great impact due to the variableness of involved parameters, they have good applications in multi-attribute decision making (MADM) under fuzzy sets (FSs) construction. Recently, Senapati et al. (2022) developed Aczel-Alsina aggregation operators (AOs) under intuitionistic FSs (IFSs) and interval-valued IFSs (IVIFSs) with their applications in solving IFS and IVIFS MADM problems. We know that T-spherical FSs (TSFSs) are a recently developed approach to uncertain information with less information loss and more reliability than IFSs and IVIFSs. In this paper, we develop these AOs on TSFSs as a new approach to solve MADM problems by using Aczel-Alsina TN and Aczel-Alsina TCN under T-spherical fuzzy (TSF) information. Furthermore, the basic operations of TSF numbers (TSFNs) are developed and exemplified. Based on these operations, two types of AOs, i.e. TSF Aczel-Alsina weighted average (TSFAAWA), and TSF Aczel-Alsina weighted geometric (TSFAAWG) operators, are introduced and investigated. The reliability and accuracy of the newly developed AOs are tested numerically and theoretically by the induction methods. To further give applications and also study the sensitivity of these TSF Aczel-Alsina operators, the problem of project evaluation using these proposed operators is comprehensively observed. The results obtained by using these TSF Aczel-Alsina operators are compared with some previously existing AOs of TSFSs. According to comparison results, we observe the reliability and efficiency of the proposed methods.