What is in a Rumour

Dang, Anh Duc; Moh’d, Abidalrahman; Milios, Evangelos; Minghim, Rosane

doi:10.1145/2949035.2949040

Cited by 9 publications

(4 citation statements)

References 12 publications

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“…First, we generated n-gram sets of frequencies (Zhou et al, 2017): a contiguous sequence of n words from a given sequence of text (Rizkallah, Atiya, Mahgoub, & Heragy, 2018). N-gram is widely used in natural language processing (NLP) applications such as speech recognition, machine translation, and information retrieval (Dang et al, 2016). Next, we made use of the “bag-of-words” (BoW) technique, known as the most common method for text analysis based on NLP (Razavi, Matwin, De Koninck, & Amini, 2014).…”

Section: Methodsmentioning

confidence: 99%

Rape narratives analysis through natural language processing: Survivor self-label, narrative time span, faith, and rape terminology.

Levy¹,

Eckhaus²

2020

Psychological Trauma: Theory, Research, Practice, and Policy

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Rape-survivor identity is a sign of recovery and positive therapeutic progress among rape victims. This study is one of the few to focus on factors predicting self-labeling as a survivor among self-acknowledged rape victims by evaluating the contribution of the time span of the rape narrative, rape terminology, and expression of faith. Method: The data were elicited from 3,794 rape narratives published on Brave Miss World, a website established, inter alia, to allow rape victims to share their stories. To identify the key concepts within rape narratives, we performed text mining based on natural language processing (NLP) and developed a model. Structural equation modeling (SEM) was used to test the model's goodness-of-fit analysis. Results: The results indicated a good fit between the theoretical model and the data. Time predicted expressions of faith and the use of rape terminology, and there was a positive correlation between faith and the use of rape terminology. Both expressions of faith and the use of rape terminology mediated between time span and self-labeling as a survivor, with a significant positive effect on self-labeling as a survivor. Conclusions: The results suggest that addressing rapevictim faith and the use of rape terminology in the depiction of their sexual trauma may be beneficial for the therapeutic process and postrape recovery. Clinical Impact StatementThis research suggests that practitioners working with victims of sexual victimization should address victims' postrape spiritual state and development. Also, this study highlights the importance of the terminology used by victims of rape and sexual assault when describing their traumatic experiences.

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Section: Methodsmentioning

confidence: 99%

Rape narratives analysis through natural language processing: Survivor self-label, narrative time span, faith, and rape terminology.

Levy¹,

Eckhaus²

2020

Psychological Trauma: Theory, Research, Practice, and Policy

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“…In this field, human computer-interaction is recorded to evaluate the user with respect to a specific research interest. The approach is used in several areas such e-commerce and online social networks research to create services like recommendation systems (Plumbaum et al, 2009) or to analyze social behavior (Dang et al, 2016). There is no case of user activity analysis related to electronic administration specifications, using process mining techniques in combination with semantic reasoning.…”

Section: Related Workmentioning

confidence: 99%

Mining Self-Defined Business Process in Electronic Administration

Lamghari

Saidi

Radgui

et al. 2022

International Journal of E-Services and Mobile Applications

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The information retrieval system is a set of resources and tools that allow users to search for information in a given domain. This system permits users to perform their research according to their objectives in diverse ways producing different behaviors. Even users with the same objective may follow different paths and stand different sub-processes, which are introduced as self-defined Business Processes that vary in terms of structure, objective, and result. This puts forward the difficulty of obtaining and studying these user’s behaviors. This paper targets the problem of representing and managing self-defined business process variability. A special interest is given to the use of process mining to deal with this challenge. In this regard, a case study about citizens in interaction with the Electronic Administration is presented, to discover and manage variability of this process type. The main result is a set of recommendations to end users.

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“…• TwitterTrails (Metaxas et al, 2015) is an interactive, web-based tool that visualises the origin and propagation characteristics of a rumour and its refutation, on Twitter. Another visualisation-based framework for studying rumour propagation is RumourFlow (Dang et al, 2016).…”

Section: Related Workmentioning

confidence: 99%

Journalist-in-the-Loop: Continuous Learning as a Service for Rumour Analysis

Karmakharm¹,

Αλέτρας²,

Bontcheva³

2019

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conferen

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Automatically identifying rumours in social media and assessing their veracity is an important task with downstream applications in journalism. A significant challenge is how to keep rumour analysis tools up-to-date as new information becomes available for particular rumours that spread in a social network. This paper presents a novel open-source webbased rumour analysis tool that can continuous learn from journalists. The system features a rumour annotation service that allows journalists to easily provide feedback for a given social media post through a web-based interface. The feedback allows the system to improve an underlying state-of-the-art neural networkbased rumour classification model. The system can be easily integrated as a service into existing tools and platforms used by journalists using a REST API.

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What is in a Rumour

Cited by 9 publications

References 12 publications

Rape narratives analysis through natural language processing: Survivor self-label, narrative time span, faith, and rape terminology.

Rape narratives analysis through natural language processing: Survivor self-label, narrative time span, faith, and rape terminology.

Mining Self-Defined Business Process in Electronic Administration

Journalist-in-the-Loop: Continuous Learning as a Service for Rumour Analysis

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