Dynamic features based rumor detection method

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August undefined, 2024

WebApr 11, 2024 · Besides, Liu et al. presented a rumor detection model based on convolution neural network (CNN), vectorized the rumor events in microblogs and mined the deep features of texts through the learning and training of hidden layer of CNN, which avoided the problem of feature construction. The rumor events detection methods based on … WebMay 6, 2024 · Most existing methods learn event-specific features that can not be transferred to unseen events. This paper proposed an end-to-end framework named Event Adversarial Neural Network (EANN), which can derive event-invariant features with adversarial learning and thus benefit the detection of fake news on newly arrived …

Dual Co-Attention-Based Multi-Feature Fusion Method …

WebOct 6, 2024 · Rumor detection methods are mainly divided into two categories—content feature-based methods and propagation structure-based methods. The methods based on content features mainly use … WebMay 1, 2024 · Therefore, some researchers study rumor detection methods based on the semantic information of posts and their dissemination structure. For example, Ma et al. [16] develope a tree-structured neural network to capture the semantic information and propagation thread. ... [28] integrate the static features such as basic user information … find data type matlab

Dynamic Features Based Rumor Detection Method

WebFeb 27, 2024 · However, epidemic rumors provide limited signal features in the early stage. In order to identify rumors with data sparsity, we propose a few-shot learning rumor detection model based on capsule networks (CNFRD), utilizing the metric learning framework and the capsule network to detect the rumors posted during unexpected … WebMay 12, 2024 · The social network has become the primary medium of rumor propagation. Moreover, manual identification of rumors is extremely time-consuming and laborious. It is crucial to identify rumors … WebOct 6, 2024 · Online rumors spread rapidly through social media, which is a great threat to public safety. Existing solutions are mainly based on content features or propagation structures for rumor detection. However, due … gtpc milton keynes and gtpc manila

Combining Temporal and Interactive Features for Rumor …

Rumor detection driven by graph attention capsule network on …

WebJan 17, 2024 · Social media has been developing rapidly in public due to its nature of spreading new information, which leads to rumors being circulated. Meanwhile, detecting rumors from such massive information in social media is becoming an arduous challenge. Therefore, some deep learning methods are applied to discover rumors through the … WebAug 27, 2024 · Finally, we fuse the structure representation and content features into a unified framework for effective rumor detection. Experimental results on two real-world social media datasets demonstrate the salience of dynamic propagation structure information and the effectiveness of our proposed method in capturing the dynamic … find data type in pysparkWebApr 20, 2024 · A novel two-layer GRU model for rumor events detection based on a Sentiment Dictionary and a dynamic time series (DTS) algorithm, named as SD-DTS-GRU, which learns continuous representations of microblog events in a better manner by making use of the SD to identify fine-grained human emotional expressions of each event and … find data type in oracle

"WebMay 12, 2024 · In this paper, a deep neural network- (DNN-) based feature aggregation modeling method is proposed, which makes full use of the knowledge of propagation pattern feature and text content feature of … " - Dynamic features based rumor detection method

Dynamic features based rumor detection method

Call Attention to Rumors: Deep Attention Based Recurrent Neural ...

WebRumor detection on social media is a task of classifying messages or posts with their veracity labels. Traditional approaches in rumor detection and other misinformation detection are to extract handcrafted features with prior knowledge on rumors. The content-based method and user-based method were two main approaches [7–9, 11]. WebSince deep learning- based methods offer promising solutions in this area, we majorly discuss the baseline methods related to deep-based unimodal and multimodal fake news detection. 2.1 Unimodal fake news detection Jae-Seung Shim et al. [13] proposed a context-based approach that utilizes the network information of the user and vectorizes it …

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WebAug 1, 2024 · Traditional feature-based approaches extract features from the false rumor message, its author, as well as the statistics of its responses to form a flat feature vector. WebExisting work on rumor detection concentrates more on the utilization of textual features, but diffusion structure itself can provide critical propagating information in identifying …

Websentiment features into rumor detection. Wu et al. [10] proposed to capture the high-order propagation patterns to improve rumor detection. Most of these feature-based methods are biased, time-consuming and limited. They are usually designed for speciﬁc scenarios and hence cannot be easily generalized for other appli-cations. WebThe ODE-based dynamic module leverages a GCN integrated with an ordinary differential system to explore dynamic features of heterogeneous graphs. To evaluate the …

WebPrevious methods for rumor detection focused on mining features from content and propagation patterns but neglected the dynamic features with joint content and propagation pattern. In this paper, we propose a novel heterogeneous GCN-based method for dynamic rumor detection (HDGCN), mainly composed of a joint content and propagation module … WebNov 15, 2024 · Currently, most rumor detection methods and fake news detection methods are supervised. The most common type is the content-based methods. The content-based methods classify rumors or fake news depending on the veracity of text or images. These work assume that, the content in different types of rumors (or news) …

WebDec 16, 2024 · A rumor detection model that combines temporal and interactive features is proposed, taking full account of rumor’s features. By using the DFT algorithm, the …

WebAug 18, 2024 · In Fig 3, we illustrated the two different methods of snapshot generations. Here on the index i for the claim ci will be omitted. S(t) is the graph snapshot at the time step t. Each graph snapshot in S will have separate adjacency matrices A = { A(1), A(2), , A(T) } with S(t) = V(t), E(t). Fig 3. find datatype in pysparkWebAug 11, 2024 · Dynamic Features Based Rumor Detection Method. Abstract: Rumor detection is a hot research issue, and this technology is widely used in various social sites such as Facebook, Twitter and Weibo. The existing rumor detection technologies are … find datatype in phpWebOct 12, 2024 · Rumor detection methods based on propagation structure usually analyze the propagation paths or networks formed by retweets and comments of blog posts to … find data type in phpWebApr 5, 2024 · The lexicon-based sentiment classification method classifies the sentiment of text by using the statistical features of sentiment from researchers’ experience or experts’ opinions etc. This kind of method needs to continuously expand the lexicon and some new words, and its accuracy rate of text sentiment analysis is not high enough. find datatype in oracle sqlWebApr 4, 2024 · The dynamic rumor influence minimization (DRIM) problem is introduced, a step-by-step discrete time optimization method for controlling rumors and a dynamic rumor-blocking approach, namely RLDB, based on deep reinforcement learning is provided. Spreading malicious rumors on social networks such as Facebook, Twitter, … find datatype in sqlWebAug 18, 2024 · Thus, detecting the rumors and preventing their spread became an essential task. Some of the recent deep learning-based rumor detection methods, such as Bi-Directional Graph Convolutional Networks (Bi-GCN), represent rumor using the completed stage of the rumor diffusion and try to learn the structural information from it. gtp commandWebconsider the event-level rumor detection task. There is a set of posts in each event and the objective is to identify whether the event is a rumor by leverage the posts in it. Below we summarize the related work on rumor detection based on the information they utilize. Most content-based methods leverage the characteristics gtp cloth for sale in ghana