activity
20182022
most citedDigital Information Seeking and Sharing Behavior During the First Wave of the COVID-19 Pandemic

1 citations · 1 across the 2 of their papers we have counts for

collaborators

7 papers

cs.SI20221 cited

Digital Information Seeking and Sharing Behavior During the First Wave of the COVID-19 Pandemic

Mehak Fatima, Aimal Rextin, Mehwish Nasim +1

People turn to search engines and social media to seek information during population-level events, such as during civil unrest, disease outbreaks, fires, or flood. They also tend t…

cs.SI2022

Are we always in strife? A longitudinal study of the echo chamber effect in the Australian Twittersphere

Mehwish Nasim, Derek Weber, Tobin South +4

Contrary to expectations that the increased connectivity offered by the internet and particularly Online Social Networks (OSNs) would result in broad consensus on contentious issue…

cs.SI2020

#ArsonEmergency and Australia's "Black Summer": Polarisation and misinformation on social media

Derek Weber, Mehwish Nasim, Lucia Falzon +1

During the summer of 2019-20, while Australia suffered unprecedented bushfires across the country, false narratives regarding arson and limited backburning spread quickly on Twitte…

cs.CR2019

Gathering Cyber Threat Intelligence from Twitter Using Novelty Classification

Ba Dung Le, Guanhua Wang, Mehwish Nasim +1

Preventing organizations from Cyber exploits needs timely intelligence about Cyber vulnerabilities and attacks, referred as threats. Cyber threat intelligence can be extracted from…

cs.SI2018

Analysing Emergent Users' Text Messages Data and Exploring its Benefits

Anas Bilal, Aimal Rextin, Ahmad Kakakhail +1

While users in the developed world can choose to adopt the technology that suits their needs, the emergent users cannot afford this luxury, hence, they adapt themselves to the tech…

cs.CY2018

Pachinko Prediction: A Bayesian method for event prediction from social media data

Jonathan Tuke, Andrew Nguyen, Mehwish Nasim +4

The combination of large open data sources with machine learning approaches presents a potentially powerful way to predict events such as protest or social unrest. However, account…