Relevant bibliographies by topics / RUMOUR ANALYTICS

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'RUMOUR ANALYTICS'

Author: Grafiati
Published: 11 September 2023

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Journal articles on the topic "RUMOUR ANALYTICS"

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LI, HAIJIAO, and KUAN YANG. "ASYMPTOTIC BEHAVIOUR OF THE STOCHASTIC MAKI–THOMPSON MODEL WITH A FORGETTING MECHANISM ON OPEN POPULATIONS." ANZIAM Journal 62, no. 2 (April 2020): 185–208. http://dx.doi.org/10.1017/s1446181120000176.

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AbstractRumours have become part of our daily lives, and their spread has a negative impact on a variety of human affairs. Therefore, how to control the spread of rumours is an important topic. In this paper, we extend the classic Maki–Thompson model from a deterministic framework to a stochastic framework with a forgetting mechanism, because real-world person-to-person communications are inevitably affected by random factors. By constructing suitable stochastic Lyapunov functions, we show that the asymptotic behaviour of the stochastic rumour model is governed by the basic reproductive number. If this number is less than one, then the solution of the stochastic rumour model oscillates around the rumour-free equilibrium under extra mild conditions, indicating the extinction of the rumour with a probability of one. Otherwise, the solution always fluctuates around the endemic equilibrium under certain parametric restrictions, implying that the rumour will continually persist. In addition, we discuss a possible intervention strategy that stops the spread of rumours by strengthening the intensity of white noise, which is very different from the deterministic rumour model without white noise. Also, numerical simulations are conducted to support our analytical results.
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Harista, Tasya Salsabilla, and Muhammad Subhan. "Model Penyebaran Rumor di Media Sosial." Journal of Mathematics UNP 8, no. 2 (July 10, 2023): 93. http://dx.doi.org/10.24036/unpjomath.v8i2.14515.

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Rumors are information that spreads widely without any confirmation of truth and definite facts. One of the media that is used in rumors spreading is social media. The negative impact raised by rumors spreading through social media is the disruption of social stability, economic systems, and politics. The research purpose is to analyze the rumor spreading model on social media. This research is basic research (theoretical) using descriptive methods. The analytical results are obtained of a rumor-free equilibrium point and a rumor spread equilibrium point, each of which is asymptotic stable. The basic reproduction number obtained by the rumor will spread if the rate of movement of the population of individual who never hear the rumor or counter-rumor increases and became a individual who have been exposed to the rumor or counter-rumor.
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Putri, Arrival Rince, Muthiah As Saidah, and Mahdhivan Syafwan. "DYNAMICS OF THE RUMOR SPREADING MODEL OF INDONESIA TWITTER CASE." BAREKENG: Jurnal Ilmu Matematika dan Terapan 16, no. 2 (June 1, 2022): 625–34. http://dx.doi.org/10.30598/barekengvol16iss2pp625-634.

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The study of the spreading of a rumor is significantly important to obtain scientific information and better strategies in reducing its negative impact. Twitter has become a medium for spreading rumors or hoaxes spatially and chronologically because it has a unique community structure. This study demonstrates the model of spreading rumors by considering credibility, correlation, and mass classification based on personality is discussed. The behavior of a model solution around equilibrium points is investigated with the Jacobian matrices. The stability also corresponds to a threshold number indicating the rumor fades away or continues to spread in the population. The analytical results are confirmed by actual data from Twitter in Indonesia with #SahkanRUUPKS. The simulation results show that the free rumor equilibrium point is stable and the threshold number is less than 1. Our study shows that the number of spreaders does not increase and the #SahkanRUUPKS rumor will vanish.
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Chen, Jianhong, Chaoqun Chen, Qinghua Song, Yifei Zhao, Longxin Deng, Raoqing Xie, and Shan Yang. "Spread Mechanism and Control Strategies of Rumor Propagation Model Considering Rumor Refutation and Information Feedback in Emergency Management." Symmetry 13, no. 9 (September 14, 2021): 1694. http://dx.doi.org/10.3390/sym13091694.

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The rumor-free equilibrium state and rumor-endemic equilibrium state are two symmetric descriptions of the status of a system. The constant spreading of rumors would affect the smooth operation of emergency management procedures and cause unnecessary social and economic loss. To reduce the negative effect of rumor propagation, in this paper, we introduce a compartmental model of rumor propagation, which considers the rumor refutation of public and information feedback. By deriving mean-field equations that describe the dynamics of the model, we use analytical and numerical solutions of these equations to investigate the threshold and dynamics of the model in both the closed system and open system. The results imply that the initial equilibrium point is not stable and there exists a rumor-free equilibrium point; in the open system, there exists a threshold beyond which rumors can spread; the stability of the initial equilibrium point is related to the threshold R0 = (φ*α)/μ, and there exists a rumor-endemic equilibrium point. The development process of rumor propagation can be divided into four stages: latent period, progressive period, intense period, and recession period. Under the influence of population, rumor spreading can exceed the threshold readily because the migration rate μ is usually less than the proportion of ignorants without critical ability φ, and the rumor spreading process in an open system presents a fluctuating development, the rumor would not disappear in this autonomous system. Based on the analysis, we propose some measures, such as providing open and efficient information queries and exchange platforms, etc.
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Huo, Liang’an, Tingting Lin, Chen Liu, and Xing Fang. "How the node’s vital and tie strength effect rumor spreading on social network." International Journal of Modern Physics C 30, no. 06 (June 2019): 1950046. http://dx.doi.org/10.1142/s0129183119500463.

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The spread of rumors on complex networks has attracted wide attention in the field of management. In this paper, the generalized rumor spreading model is modified to take into account the vital of the spreader and the tie strength for the pairwise contacts between nodes in complex networks at degree-dependent spreading rate. Concretely, we introduce the infectivity exponent [Formula: see text], and the degree influenced real exponent [Formula: see text] into the analytical rumor spreading model. Rumor infectivity, [Formula: see text], where [Formula: see text], defines that each spreader node may contact [Formula: see text] neighbors within one time step. The tie strength between two nodes with degrees [Formula: see text] and [Formula: see text] are measured by [Formula: see text], [Formula: see text] is the degree influenced real exponent which depends on the type of complex networks and [Formula: see text] is a positive quantity. We use a tuning parameter [Formula: see text] to combine both the effect of the vital nodes and the strength of connectivity between nodes. We use analytical and numerical solutions to examine the threshold behavior and dynamics of the model on several models of social network. It was found that the infectivity exponent [Formula: see text], the degree influenced real exponent [Formula: see text] and tuning parameter [Formula: see text] affect the rumor threshold, one can adjust the parameters to control the rumor threshold which is absent for the standard rumor spreading model.
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Ni, Shiwen, Jiawen Li, and Hung-Yu Kao. "HAT4RD: Hierarchical Adversarial Training for Rumor Detection in Social Media." Sensors 22, no. 17 (September 2, 2022): 6652. http://dx.doi.org/10.3390/s22176652.

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With the development of social media, social communication has changed. While this facilitates people’s communication and access to information, it also provides an ideal platform for spreading rumors. In normal or critical situations, rumors can affect people’s judgment and even endanger social security. However, natural language is high-dimensional and sparse, and the same rumor may be expressed in hundreds of ways on social media. As such, the robustness and generalization of the current rumor detection model are in question. We proposed a novel hierarchical adversarial training method for rumor detection (HAT4RD) on social media. Specifically, HAT4RD is based on gradient ascent by adding adversarial perturbations to the embedding layers of post-level and event-level modules to deceive the detector. At the same time, the detector uses stochastic gradient descent to minimize the adversarial risk to learn a more robust model. In this way, the post-level and event-level sample spaces are enhanced, and we verified the robustness of our model under a variety of adversarial attacks. Moreover, visual experiments indicate that the proposed model drifts into an area with a flat loss landscape, thereby, leading to better generalization. We evaluate our proposed method on three public rumor datasets from two commonly used social platforms (Twitter and Weibo). Our experimental results demonstrate that our model achieved better results compared with the state-of-the-art methods.
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Aloweidi, Abdelkarim, Isam Bsisu, Aiman Suleiman, Sami Abu-Halaweh, Mahmoud Almustafa, Mohammad Aqel, Aous Amro, et al. "Hesitancy towards COVID-19 Vaccines: An Analytical Cross–Sectional Study." International Journal of Environmental Research and Public Health 18, no. 10 (May 12, 2021): 5111. http://dx.doi.org/10.3390/ijerph18105111.

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Vaccination is the most promising strategy to counter the spread of Coronavirus Disease 2019 (COVID-19). Vaccine hesitancy is a serious global phenomenon, and therefore the aim of this cross-sectional study was to explore the effect of educational background, work field, and social media on attitudes towards vaccination in Jordan. We compared between medical personnel who were in direct contact with patients and non-medical individuals at Jordan University Hospital in terms of demographics, knowledge about COVID-19 vaccines, rumors received via social media, their trust in these vaccines, and the encouraging factors for vaccination. 646 individuals were enrolled in this study, of which 287 (44.4%) were from medical field, and 359 (55.6%) from non-medical field. 226 (35%) were planning to take the vaccine once available, with a positive response from 131 (45.6%) medical field workers, compared to 94 (26.2%) non-medical individuals (p < 0.001). The social media rumor that was believed the most was the unsafety of these vaccines (n = 283; 43.8%). Only 163 (56.8%) of medical persons did not believe any of the circulated rumors, compared to 126 (35.1%) of non-medical persons (p < 0.001). The effect of medical personnel advice (OR = 0.83; 95% CI = 0.70 to 0.98; p = 0.026) and social media (OR = 1.21; 95% CI = 1.04 to 1.41; p = 0.012) were significantly associated with the willingness to take COVID-19 vaccine once available. In conclusion, medical personnel and social media play a crucial role in increasing the society’s inclination towards vaccination by providing the community with updated evidence-based information about COVID-19 vaccines as an efficient medical countermeasure and by correcting the previously spread misinformation.
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ALSHIBLE, Mohamad. "Social Media Rumors in Time of Corona Pandemic, Why & How is Criminalized? (Comparative Study)." Journal of Advanced Research in Law and Economics 9, no. 3 (June 15, 2020): 719. http://dx.doi.org/10.14505/jarle.v11.3(49).03.

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No one in the world does not know what Corona is as a global pandemic, which the Secretary-General of the WHO has declared as ‘the enemy of humanity’. Yes, it is the enemy of humanity; the whole humans rose up to prevent it through several aspects. We are – as lawmen – responsible for the legal sides. All of us have become so miserable that many sciences are terrified of rumors and false news. The real news leaves pain in the souls, so what about that are false, whether it was broadcast or transmitted with intent or unintentionally The main objective of this article is to examine the Jordanian legislator attitude in regard of social media rumors during Corona pandemic (COVID19), in comparative to the Chinese legislator. The study shows that the opportunity to punish rumors at the time of the pandemic may be unavailable or weak and not coherent in Jordanian laws in comparison with other legislations, especially in Chinese laws. The study will also show if rumors were included in relative International treaties. The In respect to the methodology of this article, the author followed the descriptive and analytical approaches of the related Jordanian Penal laws in comparative with the Chinese Regulations in cybercrimes, by explaining the extent to which rumor crimes is punished in Jordan according to legal methods of analysis in comparative to the Chinese legal attitude.
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de Arruda, Guilherme Ferraz, Elcio Lebensztayn, Francisco A. Rodrigues, and Pablo Martín Rodríguez. "A process of rumour scotching on finite populations." Royal Society Open Science 2, no. 9 (September 2015): 150240. http://dx.doi.org/10.1098/rsos.150240.

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Rumour spreading is a ubiquitous phenomenon in social and technological networks. Traditional models consider that the rumour is propagated by pairwise interactions between spreaders and ignorants. Only spreaders are active and may become stiflers after contacting spreaders or stiflers. Here we propose a competition-like model in which spreaders try to transmit an information, while stiflers are also active and try to scotch it. We study the influence of transmission/scotching rates and initial conditions on the qualitative behaviour of the process. An analytical treatment based on the theory of convergence of density-dependent Markov chains is developed to analyse how the final proportion of ignorants behaves asymptotically in a finite homogeneously mixing population. We perform Monte Carlo simulations in random graphs and scale-free networks and verify that the results obtained for homogeneously mixing populations can be approximated for random graphs, but are not suitable for scale-free networks. Furthermore, regarding the process on a heterogeneous mixing population, we obtain a set of differential equations that describes the time evolution of the probability that an individual is in each state. Our model can also be applied for studying systems in which informed agents try to stop the rumour propagation, or for describing related susceptible–infected–recovered systems. In addition, our results can be considered to develop optimal information dissemination strategies and approaches to control rumour propagation.
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Al-Debaisi, Abdulkareem Ali, and Muna Abujamea. "Motives for Spreading Rumors on the Internet in Jordan: An analytical study of the content of the rumors published on the " Haggak Taarf " platform." Dirasat: Human and Social Sciences 50, no. 2 (March 30, 2023): 525–38. http://dx.doi.org/10.35516/hum.v50i2.4959.

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Objectives: The objectives of this study were to determine the number and types of rumors recorded by the "Haggak" platform, which was established by the Jordanian government to address rumors published on the Internet. The study aimed to reveal the motives behind the publication of these rumors and identify the targeted parties. Methods: The survey method was adopted for this study, utilizing the content analysis form as a tool for collecting rumors, analyzing their contents, and drawing conclusions. The study sample exclusively included 62 rumors published by the platform in 2020. Results: The results showed that rumors in the health field accounted for 61% of the total, primarily due to the implementation of preventive measures during the COVID-19 pandemic. Economic rumors constituted 23% of the total, while political rumors comprised 8%. Multiple digital communication channels accounted for 35% of the sources of these rumors. WhatsApp was the second most common source, accounting for 24% of the rumors, followed by Facebook at 18%, and Twitter at 10%. Rumors originating from digital journalism accounted for 9% of the total. Conclusion: The study found that the most prominent motives for spreading rumors were, in order, misleading and falsifying facts at a rate of 52.1%, undermining citizens' confidence in the government at a rate of 17.7%, and inciting fear and terror at a rate of 15%.
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Dissertations / Theses on the topic "RUMOUR ANALYTICS"

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SHARMA, HARSHITA. "SOFT COMPUTING FOR RUMOUR ANALYTICS ON BENCHMARK TWITTER DATA." Thesis, 2019. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16701.

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As social media is a fertile ground for origin and spread of rumours, it is imperative to detect and deter rumours. Various computational models that encompass elements of learning have been studied on benchmark datasets for rumour resolution with four individual tasks, namely rumour detection, tracking, stance and veracity classification. Quick rumour detection during initial propagation phase is desirable for subsequent veracity and stance assessment. This research presents the use of adaptive and heuristic optimization to select a near-optimal set of input variables that would minimize variance and maximize generalizability of the learning model, which is highly desirable to achieve high rumour prediction accuracy. An empirical evaluation of hybrid filter-wrapper on PHEME rumour dataset is done. The features are extracted initially using the conventional term frequency-inverse document frequency (TF-IDF) statistical measure and to select an optimal feature subset two filter methods, namely, information gain and chi-square are separately combined with three swarm intelligence-based wrapper methods, cuckoo search, bat algorithm and ant colony optimization algorithm. The performance results for the combinations have been evaluated by training three classifiers (Naïve Bayes, Random Forest and J48 decision tree) and an average accuracy gain of approximately 7% is observed using hybrid filter-wrapper feature selection approaches. Chi-square filter with Cuckoo and ACO give the same maximum accuracy of 61.19% whereas Chi-square with bat gives the maximum feature reduction selecting only 17.6% iv features. The model clearly maximizes the relevance and minimizes the redundancy in feature set to build an efficient rumour detection model for social data. Due to the ever increasing use and dependence of netizens on social media, it has become a fertile ground for breeding Rumours. This work aims to propose a model for Potential Rumour Origin Detection (PROD) to enable detection of users who can be likely rumour originators. It can not only help to find the original culprit who started a rumour but can aid in veracity classification task of the rumour pipeline as well. This work uses features of the user’s account and tweet to extract meta-data. This meta-data is encoded in an 8 tuple feature vector. A credibility quotient for each user is calculated by assigning weights to each parameter. The higher the credibility of a user, less likely it is to be a rumour originator. Based on the credibility, a label is assigned to each user indicating whether it can be a potential rumour source or not. Three supervised machine learning algorithms have been used for training and evaluation and compared to a baseline zeroR classifier. The results have been evaluated on benchmark PHEME dataset and it is observed that the multi-layer perceptron classifier achieves the highest performance accuracy, that is, an average 97.26% for all five events of PHEME to detect potential rumour source.
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Book chapters on the topic "RUMOUR ANALYTICS"

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Azri, Abderrazek, Cécile Favre, Nouria Harbi, Jérôme Darmont, and Camille Noûs. "DAT@Z21: A Comprehensive Multimodal Dataset for Rumor Classification in Microblogs." In Big Data Analytics and Knowledge Discovery, 161–75. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-39831-5_16.

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Sadat Aothoi, Mehzabin, Samin Ahsan, Najeefa Nikhat Choudhury, and Annajiat Alim Rasel. "Supervised Hybrid Model for Rumor Classification: A Comparative Study of Machine and Deep Learning Approaches." In Big Data Analytics and Knowledge Discovery, 281–86. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-39831-5_25.

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Bugueño, Margarita, Gabriel Sepulveda, and Marcelo Mendoza. "An Empirical Analysis of Rumor Detection on Microblogs with Recurrent Neural Networks." In Social Computing and Social Media. Design, Human Behavior and Analytics, 293–310. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21902-4_21.

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Koohikamali, Mehrdad, and Dan J. Kim. "Rumor and Truth Spreading Patterns on Social Network Sites During Social Crisis: Big Data Analytics Approach." In Lecture Notes in Business Information Processing, 166–70. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45408-5_15.

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Conference papers on the topic "RUMOUR ANALYTICS"

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Li, Beibei, Xueli Liu, Bowen Dong, Wenjun Wang, and Bike Zhang. "Personalized Rumor Refutation Through Graph Regular Pattern." In 2023 IEEE 8th International Conference on Big Data Analytics (ICBDA). IEEE, 2023. http://dx.doi.org/10.1109/icbda57405.2023.10104992.

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Zhao, Zhenyu, and Xi Chen. "Propagation Model of Derivative Rumor Considering Propagation Error and Malicious Tampering." In 2019 IEEE 4th International Conference on Big Data Analytics (ICBDA). IEEE, 2019. http://dx.doi.org/10.1109/icbda.2019.8713229.

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Lin, Hongbin, Xi Zhang, and Xianghua Fu. "A Graph Convolutional Encoder and Decoder Model for Rumor Detection." In 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2020. http://dx.doi.org/10.1109/dsaa49011.2020.00043.

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Nie, H. Ruda, Xiuzhen Zhang, Minyi Li, and Anil Dolgun. "Mitigation of Rumours in Social Networks via Epidemic Model-based Reinforcement Learning." In 2022 IEEE 9th International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2022. http://dx.doi.org/10.1109/dsaa54385.2022.10032384.

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Nie, H. Ruda, Xiuzhen Zhang, Minyi Li, Anil Dolgun, and James Baglin. "Modelling User Influence and Rumor Propagation on Twitter using Hawkes Processes." In 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA). IEEE, 2020. http://dx.doi.org/10.1109/dsaa49011.2020.00090.

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Doerr, Benjamin, and Marvin Künnemann. "Tight Analysis of Randomized Rumor Spreading in Complete Graphs." In 2014 Proceedings of the Eleventh Workshop on Analytic Algorithmics and Combinatorics (ANALCO). Philadelphia, PA: Society for Industrial and Applied Mathematics, 2013. http://dx.doi.org/10.1137/1.9781611973204.8.

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Yu, Ze, Gang Zhou, Junyong Luo, Mengli Zhang, and Ningbo Huang. "Stability Analysis of a Rumor Propagation Model in Complex Networks with Holling II Type Functional Response." In 2020 6th International Conference on Big Data and Information Analytics (BigDIA). IEEE, 2020. http://dx.doi.org/10.1109/bigdia51454.2020.00056.

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Ulizko, Mikhail, Evheniy Tretyakov, Rufina Tukumbetova, Alexey Artamonov, and Mikhail Esaulov. "Visualization of Dataflows: a Casestudy of COVID-19 Rumors." In 31th International Conference on Computer Graphics and Vision. Keldysh Institute of Applied Mathematics, 2021. http://dx.doi.org/10.20948/graphicon-2021-3027-259-267.

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One of the most significant and rapidly developing works in the field of data analysis is information flow management. Within the analysis targeted and stochastic dissemination patterns are studied. The solving of such problems is relevant due to the global growth in the amount of information and its availability for a wide range of users. The paper presents a study of dissemination of information messages in open networks on the example of COVID-19. The study was conducted with the use of visual analytics. Informational messages from the largest world and Russian information services, social networks and instant messengers were used as sources of information. Due to the large amount of information on the topic, the authors proposed a pattern of the wave-like dissemination of information on the example of topic clusters on the connection of COVID-19, hydroxychloroquine and 5G. The developed methods can be scaled up to analyze information events of various topics.
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Wilderom, Mariana Martínez. "Espaço educacional contemporâneo reflexões sobre os rumos da arquitetura escolar na cidade de São Paulo (1935-2013)." In Seminario Internacional de Investigación en Urbanismo. Barcelona: Facultad de Arquitectura. Universidad de la República, 2015. http://dx.doi.org/10.5821/siiu.6235.

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O artigo analisa a história do espaço educacional na cidade de São Paulo a partir do Centro Educacional Unificado, um complexo de equipamentos educacionais, culturais e recreativos, implantados pela prefeitura de São Paulo (2002-2004), nos bairros periféricos carentes de equipamentos sociais, espaços públicos e infraestrutura urbana. O CEU foi aclamado por seus idealizadores e pela mídia especializada, como um indutor de urbanidade, pois cria um espaço público diferenciado, que remete à cidade formal, atendendo o público escolar e a comunidade local. Esta análise histórica se desenvolve a partir de três eixos temáticos que consideram a escola como política pública, tipologia arquitetônica e intervenção urbana. É a partir dessa estrutura analítica que se buscou compreender como o equipamento educacional chegou a esse modelo que, ao condominializar uma série de equipamentos tradicionalmente distribuídos pela cidade, equaliza a oferta de serviços a populações carentes, mas tensiona as relações entre a escola e cidade. This article develops an analysis on the history of educational spaces in São Paulo, based on contemporary issues involving the Centro Educacional Unificado (CEU, Unified Educational Center) a complex of educational, cultural and recreational institutions, deployed by the city of São Paulo(2002-2004), in the low-income areas that showed a lack of social facilities, public spaces and urban infrastructure. CEUs were hailed by their developers and specialized media as urbanity inductors because they create a distinctive public space, which referred to the formal city, serving both the public and the local school community.This historical analysis is read from three points of view: the school is at the same time a public policy, an architectural typology and an urban intervention.Studying that analytical framework, this work sought the understanding on how the regular public schools ended up becoming this multi-proposal facility which groups a series of institutions that were traditionally distributed through the city, equalizing the provision of services to underserved populations,however stresses the relation between the school and the city.
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