Milindu Tissera, Author at LIRNEasia


“In October 2006, the Government mandated a 50% margin deposit on the invoiced value of 44 listed items.” However, in September 2021, “the margin deposit is 100% for a much larger list.
“A LIRNEasia focus study conducted in Gampaha during Sri Lanka’s second pandemic lockdown last year found that only 48 per cent of households with children had access to a smartphone or a computer and only a third of households with children had an internet connection. This (34 per cent) is on average: poorer, rural households are systematically worse off as the number drops to 21 per cent in the lowest socioeconomic group households.
A Panel discussion organised by the Computer Society of Sri Lanka focusing on Digital Citizenship, Safety and Hygiene was held on 31st August 2021. The event sponsored by Facebook brought together six panelists including LIRNEasia Chair Prof. Rohan Samarajiva, who shared his expertise.
The Institute of Chartered Professional Managers of Sri Lanka’s (CPM Sri Lanka) 26th Webinar was held on the 27th of August 2021 with a focus on the ‘Safety of information in a technically driven world’ a timely subject of cyber security. LIRNEasia Chair Prof. Rohan Samarajiva, shared his expertise on the key presentation (below) focusing on the current issues of information security, including potential risks to organizations and its management, data storage and back-ups as well as prevention and recovery.
The two primary objectives of this report are to introduce a framework to assess and contextualize the Information and Communication Technology (ICT) based Assistive Technologies (ATs) that aid persons with disabilities (PWD), and to provide a comprehensive list of what can be considered as AT products with ICT components. The aforesaid framework is based on the Human Activity Assistive Technology (HAAT) Model which highlights that in disability, the technology should follow the activity-needs of the person rather than vice-versa.
The topic of transmission towers built to facilitate mobile phone service is well known and some people are of the opinion that mobile phone transmission towers are wreaking havoc on the country.
We present a dataset consisting of 3576 documents in Sinhala, drawn from Sri Lankan news websites and factchecking operations, annotated as CREDIBLE, FALSE, PARTIAL or UN- CERTAIN. The dataset has markers for the content of the document, the classification, the web domain from which each document was retrieved, and the date on which the document was published. We also present the results of misinformation classification models built for the Sinhala language, as well as comparisons to English benchmarks, and suggest that for smaller media ecosystems it may make more practical sense to model uncertainty instead of truth vs falsehood binaries.
This study looked to understand the experiences of 35 individuals during a lockdown in the Gampaha district. The last mile service delivery experiences – particularly in the areas of access to goods, education, cash and medicine – were some of the areas to which particular attention was paid.
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.
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.
Intended for policymakers, technologists, educators and others, this international collection of 19 short stories delves into AI’s cultural impacts with hesitation and wonder.