I’m Anne Crosby, and I am a first year student in Harvard Divinity School’s master of theological studies (MTS) program. I am focusing on Chinese politics, ethics, and religion.

I majored in History and East Asian Studies as an undergraduate and went on to earn a masters degree in information science. After teaching at the post-secondary level in California and earning an Ed.M., I decided to combine my interest in technology with my background in East Asian and pursue yet another masters degree.

I’m certainly not a master programmer, but I have basic coding experience, UI, and web design skills. For me the internet is about culture and human interaction—technology is a means but not an end. This course is exciting because it will be an opportunity to collaborate with some amazing classmates. I have no experience in journalism, but I love putting my info. science background to work sifting through tidbits of information and connecting the dots.

I am a consummate traveler and take every opportunity to explore the world outside of the US, spending most of my time in South and East Asia; however, Antarctica is the most incredible place I have visited. Amazing.

Things I think about sometimes:

• <i>What’s</i> the news that’s fit to print?
• <i>Who</i> the heck printed that anyway?
• Also:
o Soft power, propaganda, transnational trolling
o Networks of trust
o The role of local/localized news in civic engagement
o Net neutrality and censorship
o Internet sovereignty vs. a free and open internet

I am a religion reporter and I feel like we don’t have a great, organic understanding of religion’s role in America today. I’d like to find a way to study social media data that would help me understand where the true power centers/ideas/players are, to map out American Religion in 2017.

Here is a link to my work:

https://www.washingtonpost.com/people/michelle-boorstein/?utm_term=.7171a46bc141

The endless stream of information and content provided by social media is the worlds’s greatest gift to a reporter or researcher and also his or her worst nightmare. As helpful and empowering as crowdsourcing this kind of newsgathering or research can be, if your job is to corroborate that information it can present a minefield. How to verify the overwhelming flow of information, particularly in a breaking news, high volume context such as violence during massive demonstrations or in a conflict zone? We’ve all seen (and perhaps disparaged) people who have shared images from one conflict zone incorrectly labeled as another, whether by honest mistake or as part of a concerted propaganda campaign. But it’s all too easy to be duped by such material, particularly if shared widely in a high pressure, deadline-looming situation.

A number of people and organizations have sought to tackle this problem by creating various kinds of verification tools. A recent one is NewsCheck, a Chrome extension launched by First Draft, a coalition of organizations and places like the Google News Lab working on tools to improve skills and standards in online reporting.

The extension is a web-friendly version of a previously published guide to verification for photos and videos and essentially works by presenting the user with a checklist of considerations to run through: Are you looking at the original version? Do you know who captured the image? Do you know where the image was captured? Do you know when the image was captured? The app scores the user based on the answers and these results can be published alongside the embedded image on the intended website so that other users can see for themselves to what extent it has been possible to authenticate the information. This isn’t a perfect fix obviously and I would love to see this tool expanded to automatically feed into to some of the best and most vetted online authentication tools available, as sometimes the number of tools can be as overwhelming as the amount of content and further curation is always helpful. But it’s a nice step to attempt to systematize basic verification into workflows for anyone sharing this kind of content and to increase transparency on these efforts to readers/viewers.

After reading through the example articles on tools for journalism and storytelling, it struck me that there are so, so many resources out there for journalists. How do you keep track of all these items while collaborating with colleagues? Slack, a tool first widely adopted by the tech community, has features that will help journalists work together effectively and efficiently. It’s a messaging and collaboration tool for teams that is being rapidly adopted across industries.

• Use channels for topic specific conversations – These channels could be specific stories or even elements within a story. They can be public with your entire team or private to a specific group of people.
• Contact team members directly for one-on-one conversations using direct messaging and one-in-one calls.
• Easily share and upload files.
• Use search to easily find information. The files you upload are indexed, so search even works within PDFs.
• Use Slack integrations, like twitter and google alerts, to quickly see relevant information in appropriate channels.

Slack is primarily meant for teams and workplaces, but can be used informally also, among just a few collaborators or across many dispersed journalists. Some newsrooms, including Vox and The Associated Press, are already using the tool for collaboration. Is can also be used more widely across organizations. For example, Muckrock created a Slack team, which has recently become very popular, to help investigative journalists to retrieve data and documents from the government through the Freedom of Information Act.

Hi All!

Google Translate is a tool that most of us already know and use. As one of the more popular Google products, it currently serves 500 million monthly users. While Google Translate historically may have been helpful for casual browsers of the internet, it’s not really useful enough to rely on completely for every day conversation, nor for a comprehensive understanding of foreign website.

Google’s recent update of Google Translate, however, has changed that. As of December last year, Google introduced AI into Google Translate, making the product astoundingly better. NYTimes shares the below example:

“Uno no es lo que es por lo que escribe, sino por lo que ha leído.”
With the original Google Translate: “One is not what is for what he writes, but for what he has read.”
With the new A.I.-rendered version: “You are not what you write, but what you have read.”

The difference is stark. Not only has the improvement enabled more coherent and seamless translations, the Google Neural Machine Translation tool now is able to link between two different languages that haven’t been previously linked. That is, Google Translate (idiomatically speaking) has it’s own language that it translates all languages to, thus enabling it to translate two different languages that it hasn’t been explicitly linked to. This improvement opens the door to more language pairings without much of the previous heavy lifting of explicitly linking one language and translating it to another.

This change has interesting implications on the future of news. It makes international news articles accessible to everyone. It allows journalists much easier and faster (and more reliable) access to sources–whether it be other people or documentation and data. More data will simply be more accessible.

It also may have implications on the labor force in the news industry–local speakers may not eventually be needed for reporting. How might this change the type of coverage we get? In a time when some news articles are already written by bots, will Google Translate improve our coverage because we can “understand” more? Or will this make news stories even more impersonal and spotty as we miss cultural nuances and context that only a local expert can provide? The potential implications seem both exciting, and daunting.

Sources and more information:

Google’s AI translation tool seems to have invented its own secret internal language

[[* I reviewed the lists of tools, but understood that the selected tool does not need to be among the ones listed *]]

As a reaction to the access to huge amounts of information, we’ve seen a surge of explanatory media. Vox.com is known for its tagline “Explain the news”, theSkimm has a set of guides to hot news topics, and the tool FOLD lets writers link media cards along with their writing to provide more context.

News and storytelling already rely on images, audio, maps, cards, data diagrams, and more, to support their arguments and provide context. There is, however, an underuse of illustrations that help explain how systems work. We are visual thinkers and most of us learn better with pictures. While glorified illustrations of data and aesthetically pleasing designs are appealing, I am now talking about pictures that enable understanding by for example showing how things are connected. Future news sources that leverage this tool of explanatory illustrations, and successfully satisfy readers’ demand for understanding the news, will be at an advantage.

Figure 1: Example of an explanatory illustration

A specific tool that teaches anyone to problem-solve and communicate with pictures is Dan Roam’s book The Back of a Napkin: Solving Problems and Selling Ideas with Pictures. Dan Roam provides a methodology for discovering, developing, and selling ideas through pictures. He shows how to decompose a problem and come up with both simple pictures, as illustrated in Fig. 1, and more complex pictures.

Dan Roam describes the process of visual thinking as four steps, with separate chapters describing how to do each step:
1) looking, i.e. collecting and screening
2) seeing, i.e. selecting and clumping
3) imagining, i.e. seeing what is not there
4) showing, i.e. making it all clear

The book also includes concrete methodology charts, as shown in Figure 2, that can be useful starting points when determining how best to illustrate a topic or your ideas with pictures.

Figure 2: A chart to help determine how best to visualize a problem. The rows specify what type of problem it is (who/what, where, etc.) and the columns specify what should be highlighted (quality vs. quantity, vision vs. execution, etc.).

My name is Anushka Shah, and I work as a researcher at Ethan Zuckerman’s Center for Civic Media here at the MIT Media Lab. My work focuses on using text analytics to analyze news language and on producing research with a new analytics tool called Media Cloud.

Home is Mumbai (really, Bombay) for me. It’s where I grew up, where I went to school, and where my family lives. I studied Government and Economics in the U.K. for my undergraduate education, with the hope of returning to India to participate in the political sector. When I did return home, I slowly came to realize there were two Indias; a socially and economically comfortable one that I grew up in, and a difficult, dark, disadvantaged one that I only saw at a distance.

I spent the next three years working with non-profit organizations and grass-roots political parties trying to understand various aspects of this other India. It was an important experience for me, not because I learned much of how certain issues could be positively affected, or what policies worked on ground and didn’t, but because I understood how deeply complex rural India is.

Amidst other things, the simplistic narratives about rural India that I and many others grew up with, kept the two Indias apart. I got interested in media as a way to affect opinion, knowledge, and eventually civic engagement in India. I studied applied quantitative research with a focus on news analytics, and now work in Ethan’s lab using Media Cloud to research Indian media.

Going forward, I want to use my quantitative media skills and field experience in India to design effective media messaging back home.