Truth Decay: An Initial Exploration of the Diminishing Role of Facts and Analysis in American Public Life


Report by Jennifer Kavanagh and Michael D. Rich: “Over the past two decades, national political and civil discourse in the United States has been characterized by “Truth Decay,” defined as a set of four interrelated trends: an increasing disagreement about facts and analytical interpretations of facts and data; a blurring of the line between opinion and fact; an increase in the relative volume, and resulting influence, of opinion and personal experience over fact; and lowered trust in formerly respected sources of factual information. These trends have many causes, but this report focuses on four: characteristics of human cognitive processing, such as cognitive bias; changes in the information system, including social media and the 24-hour news cycle; competing demands on the education system that diminish time spent on media literacy and critical thinking; and polarization, both political and demographic. The most damaging consequences of Truth Decay include the erosion of civil discourse, political paralysis, alienation and disengagement of individuals from political and civic institutions, and uncertainty over national policy.

This report explores the causes and consequences of Truth Decay and how they are interrelated, and examines past eras of U.S. history to identify evidence of Truth Decay’s four trends and observe similarities with and differences from the current period. It also outlines a research agenda, a strategy for investigating the causes of Truth Decay and determining what can be done to address its causes and consequences….(More)”.

How tech used to track the flu could change the game for public health response


Cathie Anderson in the Sacramento Bee: “Tech entrepreneurs and academic researchers are tracking the spread of flu in real-time, collecting data from social media and internet-connected devices that show startling accuracy when compared against surveillance data that public health officials don’t report until a week or two later….

Smart devices and mobile apps have the potential to reshape public health alerts and responses,…, for instance, the staff of smart thermometer maker Kinsa were receiving temperature readings that augured the surge of flu patients in emergency rooms there.

Kinsa thermometers are part of the movement toward the Internet of Things – devices that automatically transmit information to a database. No personal information is shared, unless users decide to input information such as age and gender. Using data from more than 1 million devices in U.S. homes, the staff is able to track fever as it hits and use an algorithm to estimate impact for a broader population….

Computational researcher Aaron Miller worked with an epidemiological team at the University of Iowa to assess the feasibility of using Kinsa data to forecast the spread of flu. He said the team first built a model using surveillance data from the CDC and used it to forecast the spread of influenza. Then the team created a model where they integrated the data from Kinsa along with that from the CDC.

“We got predictions that were … 10 to 50 percent better at predicting the spread of flu than when we used CDC data alone,” Miller said. “Potentially, in the future, if you had granular information from the devices and you had enough information, you could imagine doing analysis on a really local level to inform things like school closings.”

While Kinsa uses readings taken in homes, academic researchers and companies such as sickweather.com are using crowdsourcing from social media networks to provide information on the spread of flu. Siddharth Shah, a transformational health industry analyst at Frost & Sullivan, pointed to an award-winning international study led by researchers at Northeastern University that tracked flu through Twitter posts and other key parameters of flu.

When compared with official influenza surveillance systems, the researchers said, the model accurately forecast the evolution of influenza up to six weeks in advance, much earlier than prior models. Such advance warnings would give health agencies significantly more time to expand upon medical resources or to alert the public to measures they can take to prevent transmission of the disease….

For now, Shah said, technology will probably only augment or complement traditional public data streams. However, he added, innovations already are changing how diseases are tracked. Chronic disease management, for instance, is going digital with devices such as Omada health that helps people with Type 2 diabetes better manage health challenges and Noom, a mobile app that helps people stop dieting and instead work toward true lifestyle change….(More).

Sub-National Democracy and Politics Through Social Media


Book edited by Mehmet Zahid Sobacı and İbrahim Hatipoğlu: “This book analyzes the impact of social media on democracy and politics at the subnational level in developed and developing countries. Over the last decade or so, social media has transformed politics. Offering political actors opportunities to organize, mobilize, and connect with constituents, voters, and supporters, social media has become an important tool in global politics as well as a force for democracy. Most of the available research literature focuses on the impact of social media at the national level; this book fills that gap by analyzing the political uses of social media at the sub-national level.

The book is divided into two parts. Part One, “Social Media for Democracy” includes chapters that analyze potential contributions of social media tools to the realizing of basic values of democracy, such as public engagement, transparency, accountability, participation and collaboration at the sub-national level. Part Two, “Social Media in Politics” focuses on the use of social media tools by political actors in political processes and activities (online campaigns, protests etc.) at the local, regional and state government levels during election and non-election periods. Combining theoretical and empirical analysis, each chapter provides evaluations of overarching issues, questions, and problems as well as real-world experiences with social media, politics, and democracy in a diverse sample of municipalities…(More)”.

Nudging the city and residents of Cape Town to save water


Leila Harris, Jiaying Zhao and Martine Visser in The Conversation: “Cape Town could become the world’s first major city to run out of water – what’s been termed Day Zero….To its credit, the city has worked with researchers at the University of Cape Town to test strategies to nudge domestic users into reducing their water use. Nudges are interventions to encourage behaviour change for better outcomes, or in this context, to achieve environmental or conservation goals.

What key insights could help inform the city’s strategies? Research from psychology and behavioural economics could prove useful to refine efforts and help to achieve further water savings.

The most effective tactics

Research suggests the following types of nudges could be effective in promoting conservation behaviours.

Social norms: International research, as well as studies conducted in Cape Town, suggest that effective conservation can be promoted by giving feedback to consumers on how they perform relative to their neighbours. To this end, Cape Town introduced a water map that highlights homes that are compliant with targets.

The city has also been bundling information on usage with easy to implement water saving tips, something that research has shown to be particularly effective.

Research also suggests that combining behavioural interventions with traditional measures – such as tariff increases and restrictions – are often effective to reduce use in the short-term.

Real-time feedback: Cape Town is presenting the daily water level in major dams on a dashboard. This approach is consistent with research that shows that real-time information can effectively reduce water and energy consumption.

Such efforts could even be more effective if information is highlighted in relation to the critical level that’s been set for Day Zero, in this case 13.5%.

In the early days of a drought, it is also advisable to make information like this readily accessible through news outlets, social media, or even text messages. The water tracker produced by eighty20, a private Cape Town-based company, provides an example.

Social recognition: There’s evidence that efforts to celebrate successes or encourage competition can be effective – for instance, recognising neighbourhoods for meeting conservation targets. Prizes needn’t be monetary. Sometimes simple recognition, such as a certificate, can be effective.

Social recognition was found to be the most successful intervention among nine others nudges tested in research conducted in Cape Town in 2016. In this experiment, households who reduced consumption by 10% were recognised on the city’s website.

Another study showed that competition between the various floors of a government building in the Western Cape led to energy savings of up to 14%.

Cooperation: In the months ahead, the city would also do well to consider the support it might offer to encourage cooperation, particularly as the situation becomes more acute and as tensions rise.

Past studies have shown that social reputation and efforts to promote reciprocity can go a long way to encourage cooperation. The point is argued in a recent article featuring the importance of cooperation among Capetonians across different income groups.

Some residents of Cape Town are already pushing for a cooperative approach such as helping neighbours who might have difficulty travelling to collection points. Support for these efforts should be an important part of policies in the run up to Day Zero. These are often the examples that provide bright spots in challenging times.

Research also suggests that to navigate moments of crisis effectively, clear and trustworthy communication is critical. This also needs to be a priority….(More)“.

Infection forecasts powered by big data


Michael Eisenstein at Nature: “…The good news is that the present era of widespread access to the Internet and digital health has created a rich reservoir of valuable data for researchers to dive into….By harvesting and combining these streams of big data with conventional ways of monitoring infectious diseases, the public-health community could gain fresh powers to catch and curb emerging outbreaks before they rage out of control.

Going viral

Data scientists at Google were the first to make a major splash using data gathered online to track infectious diseases. The Google Flu Trends algorithm, launched in November 2008, combed through hundreds of billions of users’ queries on the popular search engine to look for small increases in flu-related terms such as symptoms or vaccine availability. Initial data suggested that Google Flu Trends could accurately map the incidence of flu with a lag of roughly one day. “It was a very exciting use of these data for the purpose of public health,” says Brownstein. “It really did start a whole revolution and new field of work in query data.”

Unfortunately, Google Flu Trends faltered when it mattered the most, completely missing the onset in April 2009 of the H1N1 pandemic. The algorithm also ran into trouble later on in the pandemic. It had been trained against seasonal fluctuations of flu, says Viboud, but people’s behaviour changed in the wake of panic fuelled by media reports — and that threw off Google’s data. …

Nevertheless, its work with Internet usage data was inspirational for infectious-disease researchers. A subsequent study from a team led by Cecilia Marques-Toledo at the Federal University of Minas Gerais in Belo Horizonte, Brazil, used Twitter to get high-resolution data on the spread of dengue fever in the country. The researchers could quickly map new cases to specific cities and even predict where the disease might spread to next (C. A. Marques-Toledo et al. PLoS Negl. Trop. Dis. 11, e0005729; 2017). Similarly, Brownstein and his colleagues were able to use search data from Google and Twitter to project the spread of Zika virus in Latin America several weeks before formal outbreak declarations were made by public-health officials. Both Internet services are used widely, which makes them data-rich resources. But they are also proprietary systems for which access to data is controlled by a third party; for that reason, Generous and his colleagues have opted instead to make use of search data from Wikipedia, which is open source. “You can get the access logs, and how many people are viewing articles, which serves as a pretty good proxy for search interest,” he says.

However, the problems that sank Google Flu Trends still exist….Additionally, online activity differs for infectious conditions with a social stigma such as syphilis or AIDS, because people who are or might be affected are more likely to be concerned about privacy. Appropriate search-term selection is essential: Generous notes that initial attempts to track flu on Twitter were confounded by irrelevant tweets about ‘Bieber fever’ — a decidedly non-fatal condition affecting fans of Canadian pop star Justin Bieber.

Alternatively, researchers can go straight to the source — by using smartphone apps to ask people directly about their health. Brownstein’s team has partnered with the Skoll Global Threats Fund to develop an app called Flu Near You, through which users can voluntarily report symptoms of infection and other information. “You get more detailed demographics about age and gender and vaccination status — things that you can’t get from other sources,” says Brownstein. Ten European Union member states are involved in a similar surveillance programme known as Influenzanet, which has generally maintained 30,000–40,000 active users for seven consecutive flu seasons. These voluntary reporting systems are particularly useful for diseases such as flu, for which many people do not bother going to the doctor — although it can be hard to persuade people to participate for no immediate benefit, says Brownstein. “But we still get a good signal from the people that are willing to be a part of this.”…(More)”.

New game aims to inoculate people against fake news


Springwise: “The term ‘fake news’ has become all too common in media coverage. However, a news item doesn’t have to be entirely made up to be misleading. Many fake news stories intend to deceive, often with a political agenda. Disinformation works because many people fail to recognise false information. A recent study, conducted by Britain’s Channel 4, found that only four percent of those surveyed could tell fake news from real. So how to inoculate people against fake news? Dutch organisation DROG, which works against the spread of disinformation, has teamed up with researchers at Cambridge University in the United Kingdom to develop a game that they claim can help confer resistance against false or misleading information.

The game, titled The Bad News Game, works by putting players in the position of creating fake news, so that they gain insight into the tactics and methods used by ‘real’ fake news-mongers to spread their message. This, in turn, builds up resistance to fake news. In the game, players are shown short texts or images and can react to them in a variety of ways. Choosing an option similar to that followed by a ‘real’ producer of disinformation earns the player more followers and credibility. Lying too blatantly, choosing an option that is obviously ridiculous, or acting in line with journalistic best practices, and the player will lose followers and credibility. The aim of the game is to gather as many followers as possible without losing too much credibility.

The Bad News Game is suitable for use in schools and takes around 20 minutes to complete. It joins other recent socially conscious educational innovations such as a cooking app that encourages healthy eating and a board game that eases discussions about arranged marriages….(More)”.

When Fighting Fake News Aids Censorship


Courtney C. Radsch at Project Syndicate: “Many media analysts have rightly identified the dangers posed by “fake news,” but often overlook what the phenomenon means for journalists themselves. Not only has the term become a shorthand way to malign an entire industry; autocrats are invoking it as an excuse to jail reporters and justify censorship, often on trumped-up charges of supporting terrorism.

Around the world, the number of honest journalists jailed for publishing fake or fictitious news is at an all-time high of at least 21. As non-democratic leaders increasingly use the “fake news” backlash to clamp down on independent media, that number is likely to climb.

The United States, once a world leader in defending free speech, has retreated from this role. President Donald Trump’s Twitter tirades about “fake news” have given autocratic regimes an example by which to justify their own media crackdowns. In December, China’s state-run People’s Daily newspaper posted tweets and a Facebook post welcoming Trump’s fake news mantra, noting that it “speaks to a larger truth about Western media.” This followed the Egyptian government’s praise for the Trump administration in February 2017, when the country’s foreign ministry criticized Western journalists for their coverage of global terrorism.

And in January 2017, Turkish President Recep Tayyip Erdoğan praised Trump for berating a CNN reporter during a live news conference. Erdoğan, who criticized the network for its coverage of pro-democracy protests in Turkey in 2013, said that Trump had put the journalist “in his place.” Trump returned the compliment when he met Erdoğan a few months later. Praising his counterpart for being an ally in the fight against terrorism, Trump made no mention of Erdoğan’s own dismal record on press freedom.

It is no accident that these three countries have been quickest to embrace Trump’s “fake news” trope. China, Egypt, and Turkey jailed more than half of the world’s journalists in 2017, continuing a trend from the previous year. The international community’s silence in the face of these governments’ attacks on independent media seems to have been interpreted as consent….(More)”.

Journalism and artificial intelligence


Notes by Charlie Beckett (at LSE’s Media Policy Project Blog) : “…AI and machine learning is a big deal for journalism and news information. Possibly as important as the other developments we have seen in the last 20 years such as online platforms, digital tools and social media. My 2008 book on how journalism was being revolutionised by technology was called SuperMedia because these technologies offered extraordinary opportunities to make journalism much more efficient and effective – but also to transform what we mean by news and how we relate to it as individuals and communities. Of course, that can be super good or super bad.

Artificial intelligence and machine learning can help the news media with its three core problems:

  1. The overabundance of information and sources that leave the public confused
  2. The credibility of journalism in a world of disinformation and falling trust and literacy
  3. The Business model crisis – how can journalism become more efficient – avoiding duplication; be more engaged, add value and be relevant to the individual’s and communities’ need for quality, accurate information and informed, useful debate.

But like any technology they can also be used by bad people or for bad purposes: in journalism that can mean clickbait, misinformation, propaganda, and trolling.

Some caveats about using AI in journalism:

  1. Narratives are difficult to program. Trusted journalists are needed to understand and write meaningful stories.
  2. Artificial Intelligence needs human inputs. Skilled journalists are required to double check results and interpret them.
  3. Artificial Intelligence increases quantity, not quality. It’s still up to the editorial team and developers to decide what kind of journalism the AI will help create….(More)”.

Citicafe: conversation-based intelligent platform for citizen engagement


Paper by Amol Dumrewal et al in the Proceedings of the ACM India Joint International Conference on Data Science and Management of Data: “Community civic engagement is a new and emerging trend in urban cities driven by the mission of developing responsible citizenship. The recognition of civic potential in every citizen goes a long way in creating sustainable societies. Technology is playing a vital role in helping this mission and over the last couple of years, there have been a plethora of social media avenues to report civic issues. Sites like Twitter, Facebook, and other online portals help citizens to report issues and register complaints. These complaints are analyzed by the public services to help understand and in-turn address these issues. However, once the complaint is registered, often no formal or informal feedback is given back from these sites to the citizens. This de-motivates citizens and may deter them from registering further complaints. In addition, these sites offer no holistic information about a neighborhood to the citizens. It is useful for people to know whether there are similar complaints posted by other people in the same area, the profile of all complaints and a know-how of how and when these complaints will be addressed.

In this paper, we create a conversation-based platform CitiCafe for enhancing citizen engagement front-ended by a virtual agent with a Twitter interface. This platform back-end stores and processes information pertaining to civic complaints in a city. A Twitter based conversation service allows citizens to have a direct correspondence with CitiCafe via “tweets” and direct messages. The platform also helps citizens to (a) report problems and (b) gather information related to civic issues in different neighborhoods. This can also help, in the long run, to develop civic conversations among citizens and also between citizens and public services….(More)”.

A primer on political bots: Part one


Stuart W. Shulman et al at Data Driven Journalism: “The rise of political bots brings into sharp focus the role of automated social media accounts in today’s democratic civil society. Events during the Brexit referendum and the 2016 U.S. Presidential election revealed the scale of this issue for the first time to the majority of citizens and policy-makers. At the same time, the deployment of Russian-linked bots designed to promote pro-gun laws in the aftermath of the Florida school shooting demonstrates the state-sponsored, real-time readiness to shape, through information warfare, the dominant narratives on platforms such as Twitter. The regular news reports on these issues lead us to conclude that the foundations of democracy have become threatened by the presence of aggressive and socially disruptive bots, which aim to manipulate online political discourse.

While there is clarity on the various functions that bot accounts can be scripted to perform, as described below, the task of accurately defining this phenomenon and identifying bot accounts remains a challenge. At Texifter, we have endeavoured to bring nuance to this issue through a research project which explores the presence of automated accounts on Twitter. Initially, this project concerned itself with an attempt to identify bots which participated in online conversations around the prevailing cryptocurrency phenomenon. This article is the first in a series of three blog posts produced by the researchers at Texifter that outlines the contemporary phenomenon of Twitter bots….

Bots in their current iteration have a relatively short, albeit rapidly evolving history. Initially constructed with non-malicious intentions, it wasn’t until the late 1990s with the advent of Web 2.0 when bots began to develop a more negative reputation. Although bots have been used maliciously in denial-of-service (DDoS) attacks, spam emails, and mass identity theft, their purpose is not explicitly to incite mayhem.

Before the most recent political events, bots existed in chat rooms, operated as automated customer service agents on websites, and were a mainstay on dating websites. This familiar form of the bot is known to the majority of the general population as a “chatbot” – for instance, CleverBot was and still is a popular platform to talk to an “AI”. Another prominent example was Microsoft’s failed Twitter Chatbot Tay which made headlines in 2016 when “her” vocabulary and conversation functions were manipulated by Twitter users until “she” espoused neo-nazi views when “she” was subsequently deleted.

Image: XKCD Comic #632.

A Twitter bot is an account controlled by an algorithm or script, which is typically hosted on a cloud platform such as Heroku. They are typically, though not exclusively, scripted to conduct repetitive tasks.  For example, there are bots that retweet content containing particular keywords, reply to new followers, and direct messages to new followers; although they can be used for more complex tasks such as participating in online conversations. Bot accounts make up between 9 and 15% of all active accounts on Twitter; however, it is predicted that they account for a much greater percentage of total Twitter traffic. Twitter bots are generally not created with malicious intent; they are frequently used for online chatting or for raising the professional profile of a corporation – but their ability to pervade our online experience and shape political discourse warrants heightened scrutiny….(More)”.