A proposed change in WhatsApp’s #privacy policy has dominated headlines and prompted users worldwide to rethink their choice of messaging apps. Since then, WhatsApp has undertaken multiple efforts to clarify how the change affects users. #thread
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WhatsApp has over 400 million monthly active users in India (one-fifth of their global user base) and handles over 1 billion messages a day globally tcrn.ch/2XKWiib
WhatsApp Business claims to have 50 million users globally bit.ly/35NIeIY
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#WhatsApp also decided to push the change to May instead of February, to assuage user privacy concerns and stem the flight of users to competing apps like #Signal and #Telegram that saw millions of signups last week. cnn.it/3srOHTP
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One of the most talked about alternatives is Signal, whose commitment to privacy and minimal approach to data collection has made them the front-runner in the race for secure personal messaging apps. bit.ly/3oSYGzk
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@signalapp is a fully #opensource messaging app and is the first choice for privacy-minded users. bit.ly/3qpZ0G4
Signal is set up as a non-profit and relies on donations to fund development of the app and to keep it running. signal.org/blog/signal-fo…
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Another competitor is Telegram, an effort by Pavel Durov, a Russian entrepreneur. They offer secret chats that are end-to-end encrypted, but most other interactions in the app are not as secure. bit.ly/2Nde5fS
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Their track record with #privacy and refusal to share user data with governments has resulted in the app being banned in some countries that cite national security concerns. nytimes.com/2018/05/02/wor…
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@telegram intends to become financially sustainable using public channels (similar to a social media feed) that businesses can advertise on and offer other premium features, while keeping private chats free. t.me/durov/142
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WhatsApp’s attempts to integrate with other Facebook products began in 2016 when they started sharing Whatsapp user contact information with Facebook for analytics and targeted ads. bit.ly/2XL86AL
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In the latest change, WhatsApp has reiterated that the content of users’ messages is private thanks to end-to-end encryption faq.whatsapp.com/general/securi…
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However, their stand on linked data like user contact lists, location and usage behaviour is shaky, as they are available to them for mining/monetizing and potentially sharing with Facebook in the future. bit.ly/3oYrhU0
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Apple’s @AppStore Privacy labels provide insight into the different kinds of data that each of these messaging apps can collect and link to users.
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Here is a recent study comparing the security and privacy elements of popular messaging apps by J. Botha, C. Van ‘t Wout from @CSIR and L. Leenen @UWConline
(Link to PDF) bit.ly/2XKkGk1
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- Manage the spatial growth of cities and allow them to build more,
- Plan road networks for future horizontal expansion,
- Revoke faulty policies that constraint the use of floor space to build vertically.
3/10 || Housing: Richard Green & Sahil Gandhi
- Provide public housing for the poor; India can learn from successful models in Singapore or Hong Kong,
- Enable efficient rental markets,
- Manage density better to prevent overcrowded and unsafe housing.
#YearinReview Here is our list of 5 of the most interesting papers on state capacity this year!
Devesh Kapur's 'Why Does the Indian State Both Fail and
Succeed?' seeks to explain why India tends to have a better record on specific tasks like eradicating polio—where delivery is episodic with inbuilt exit—than on things like improving public health outcomes more generally.
Kapur proposes some explanations: understaffing of local governments, ramifications of India adopting democracy at a 'precocious' stage relative to its economic development, and the persistence of social cleavages in India by caste, gender, and religion.
Being at the forefront also posed operational and business continuity risks for the police. @_NehaSinha & @TveshaSippy addressed this risk in this blog post published by @IPF
1 - The future of cities post-pandemic
2 - Resilient dense cities
3 - Managing urban expansion
4 - Better data for policy making
5 - Financial capacity of Mumbai
6 - Costs of congestion in Mumbai
7 - Lessons from Japan
@nebuer42 and @VaidehiTandel argued that density is not to be blamed for the spread of #COVIDー19 in our cities, rather, these patterns emerged from multiple factors -@htTweets
#blogpost | Benford's law application to India's district-level #COVID19 data suggests that the quality of data is largely acceptable for decision making. (Data from @covid19indiaorg)
The 1st round of the serosurvey (July) found a seroprevalence of 54% in slums and 16% in non-slum areas and the 2nd round (Aug) found 44% in slums and 17% in non-slums. Read @muradbanaji’s analysis for more (2/5) science.thewire.in/health/mumbai-…
The difference in prevalence, herd immunity...In this insightful piece, @profmohanan summarizes the current knowledge about COVID serosurveys and addresses some of the most common questions (3/5) indianexpress.com/article/explai…