As hate speech on social media becomes an ever-increasing problem, policymakers may look to more authoritarian measures for policing content. Several countries have already, at some stage, banned networks such as Facebook and Twitter (Liebelson, 2017).
This paper presents two colloquial Sinhala language corpora from the language efforts of the Data, Analysis and Policy team of LIRNEasia, as well as a list of algorithmically derived stopwords. The larger of the two corpora spans 2010 to 2020 and contains 28,825,820 to 29,549,672 words of multilingual text posted by 533 Sri Lankan Facebook pages, including politics, media, celebrities, and other categories; the smaller corpus amounts to 5,402,76 words of only Sinhala text extracted from the larger.
We summarize the state of progress in artificial intelligence as used for classifying misinforma- tion, or ’fake news’. Making a case for AI in an assistive capacity for factchecking, we briefly examine the history of the field, divide current work into ’classical machine learning’ and ’deep learning’, and for both, examine the work that has led to certain algorithms becoming the de facto standards for this type of text classification task.
In a practical experiment, we benchmark five common text classification algorithms - Naive Bayes, Logistic Regression, Support Vector Machines, Random Forests, and eXtreme Gradient Boosting - on multiple misinformation datasets, accounting for both data-rich and data-poor environments.
Data usage in Sri Lanka has exploded by a hundred percent between March 2020 and the beginning of July 2021, with increasing complaints against service providers over speeds, connection drops and bad quality.
The COVID-19 pandemic has caused unprecedented stresses on food supply chains due to momentous shifts in demand and significant restrictions in the supply value chain and supply.
LIRNEasia Chair, Rohan Samarajiva shared a message with students in Sri Lanka who have completed their formal education on SLVLOG Good Vibes.
The network is looking to bridge some of the gaps working with various stakeholders including the Ministry of Health to provide relief to those who need it the most.
LIRNEasia Chair, Rohan Samarajiva and I attended the first drafting group meeting for developing the Asia-Pacific Information Superhighway Action Plan 2022-2026 on 25 May. The meeting was convened by UNESCAP, and chaired by Mohamed Shareef, Maldives' newly appointed State Minister of Environment, Climate Change and Technology.
Intended for policymakers, technologists, educators and others, this international collection of 19 short stories delves into AI’s cultural impacts with hesitation and wonder.
Information collection (or data collection) is vital during an epidemic, especially for purposes such as contact tracing and quarantine monitoring. However, it also poses challenges such as keeping up with the spread of the infectious disease, and the need to protect personally identifiable information. We explore some of the methods of information collection deployed in Sri Lanka and Thailand during the COVID-19 pandemic, and offer policy recommendations for future pandemics.
Responding to the COVID-19 crisis has been difficult for many. Its volatile and uncertain nature has made planning even more challenging. It is, therefore, essential that efforts are made to simplify citizens’ planning and decision-making processes to the extent possible. Our research indicates that not all citizens were adequately prepared for sudden a lockdown, despite previous experiences. Disseminating better information could help, at least to an extent.
The theme of this year's SIF was "Mobilising for Digital Resilience – a free, open, and secure internet in the shifting landscapes of the pandemic". The opening panel set the stage for discussing issues that fit under this topic, and will be followed by 2 days of further panels that explore each issue further.
Impactful utilization required a focus on outcomes: did it achieve the good that was sought to be achieved by the legislation? In general, that would require demand-side studies to see if people had been brought out of poverty, whether employment had been created, etc..
But before one gets to outcomes, it's necessary to have outputs. If the fund has not resulted in the rollout of networks or whatever it was supposed to support, there is not much point in looking for evidence of outcomes, good or bad.
LIRNEasia discussed policy challenges of ensuring access for all as well as the challenges of working from home during a pandemic for women at the the inaugural Sri Lanka Internet Day, organised by the Federation of Information Technology Industry Sri Lanka (FITIS) on 6-7 April 2021.
We are looking for two full-time (40 hours per week) interns to join us for a period of 12 weeks for an Internship in Machine Learning and Remote Sensing