Tag Archives: OpenNews

OpenNews 3D Prints


After several weeks of waiting, we finally got 3D prints in for our enclosures! We had hoped to have these ready for ICAT day; however, the prints ended up taking much longer than estimated by the library’s Design Studio. The Raspberry Pi enclosure ended up needing to be printed twice after the first 3D printer malfunctioned and printed an unusable hunk of plastic. As you can see in the photos below, the prints were still imperfect, but fit together well and would have been ideal for a quick prototype demonstration.

We modeled an enclosure for our buttons to fit in with space for LEDs and wires. We also downloaded a 3D model for our raspberry pi enclosure from thingiverse.


Ultimately, we were able to make-do with our quick cardboard version of the enclosure, which was more than sufficient for our purposes, especially considering the technical issues we encountered during our presentation that made the buttons less than functional.

In the future, it might be a better idea to allow for several weeks for printing time to account for potential 3D printer delays and malfunctions.

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Group 5 – OpenNews: Critical Response


In this update, we will discuss and address some of the concerns that were brought to our attention by various critics of our system. We have chosen to omit generally positive comments and focus on areas that need improvement and better definition.

Notable Responses

Reviewer: Kari

Process and Methods: 5 / 5. “Lots of supporting documentation/research. I wish they approached them them with a more [unknown word] eye”.
Response: That is true, during our research we may have been looking for evidence that supports trends rather than evidence that does not.

Quality of Proposed System: 3 / 5. “I’m concerned about the desire to eliminate bias from news, as we discussed during the feedback session. The aims are [unknown], just I’m not sure that the prototype will accomplish them”. Response: I think the reviewer is pointing out that we may have issues eliminating bias in our prototype or that our prototype will not be robust enough to demonstrate. I believe this is something we will address more closely in the coming weeks as we begin to flush out our presentation ideas. Ultimately, we realize that our idea is too ambitious to fully implement; however, we believe we can implement aspects (including a rudimentary classification system) that will create a compelling argument for the existence of our entire system. 

Reviewer: Ellis

Process and Methods: 4 / 5. “I was curious about related work. I saw a lot of what was wrong but not of anything with similar solution”.
Response: This comment indicates the importance of understanding our system and where it gets its roots. That is to say, we should have done and should do more research and examination of similar existing system such as Wikinews and Politifact in order to clearly demonstrate how we will address the weak points and problems with these. Generally, we believe our system gets it strength and distinction from having an intuitive and clean user experience, a robust natural language processing backend, and a strong crowd driven experience with defined checks and balances.

Reviewer: Wisnioski

Presentation and Communication: 3 / 5. “Strong desire to tackle key issue. Is objectivity possible in a media environment?”
Response: We need to research and analyze whether objectivity really
is possible in a media environment and present that in a clear manner. We believe this really comes down to better defining how we are quantifying the quality of news and preventing the introduction of slow-moving, hard-to-see algorithmic biases. We will begin to address this more closely in the coming weeks as we begin to think about our prototype more.

Process and Methods: 3.5 / 5. “Lots of exciting literature on this. What systems currently exist? (re: politifact). Response: This question was addressed two comments up. The fact that it came up again indicates that we should prioritize this discussion.

Quality of Proposed System: 3.5 / 5. “Important domain space, I suggest focusing on an element of “news” that especially fits your model”.
Response: We should identify and then focus on different elements of news. We likely do not know enough
about news itself.

Reviewer: Zach Duer

Process and Methods: 4 / 5. Also commented next to the bullet point of “is there an appropriate review of related work and existing projects?” with “not enough” then commented “I’m deeply concerned about the idea that NLP can be trained on unbiased vs biased articles, and that it wouldn’t understand bias-by-omissions for example, and would reflect the bias of the people labeling articles as biased/unbiased for training”.
Response: We need to more clearly present our solution for avoiding bias in labeling, which is crowdsourcing to people from all demographics and having each article reach a certain percent agreement on whether or not it is biased. Bias by omission is a strong concern but we are hoping that the open source aspect of OpenNews will encourage those to add details that were omitted and refine algorithms.

Quality of Proposed System: 5 / 5. “Yes, great idea… is an AI for automatic first-layer WikiNews editing, makes total sense”.
Response: Let’s ensure we continue to focus on our AI and continue defining it. This is after all what makes our system unique.

Key Notes and Details

  • We need to explore and elaborate on our NLP ideas more – how do we quantify the quality of news exactly? We don’t want to focus on eliminating bias but rather making it clear when bias exists.
    • How do we keep our NLP from getting trained improperly such that biases are introduced through less obvious avenues (bias by omission)
    • How bad is bias? Is purely factual/unbiased news worth anything? We should mock up examples of what we consider to be ideal articles and unideal articles
  • There were two comments regarding pre-existing systems, noting that we should explore and understand exactly what these systems did wrong and how we’re improving on them with ours. Notably, WikiNews and Poltifact
  • We need to better define what “news” is to OpenNews

Progress Update

We’ve started mocking up some designs for OpenNews, these were shown to critics as part of the review process this post is covering. These mockups are to help us understand what news looks like and what information is important to a reader.


Article View Mockup


Homepage View Mockup

This class we’ve also determined the materials needed for our final project. So far, this includes:

We also expect to bring some monitors and computers to display our presentation, website, and possibly our movie trailer or some slideshow.

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Group 5 – Research


Secondary Research

Demographics and News Consumption

The mediums by which individuals view news vary strongly by age, gender, education and income.  


This may not seem like a problem, but the audiences of each news source varied greatly in their knowledge when asked about current events. In addition, many of these news sources are biased. Since different demographics watch different news sources, this means different demographics are exposed to different biases and amounts of direct knowledge of current events.




Algorithms and News

Many sites, such as GreatSchools and Google use algorithms to rank pages online. One issue with ranking algorithms is that they often use metrics that only subjectively indicate quality. For instance, some communities may wish to use different factors for ranking schools and often the “most viewed” page is not necessarily the highest quality. Nick Diakopoulos urges for transparency in algorithms so that consumers can choose whether or not they agree with the metrics used by the computer.



Scholarly References

Biased news distorts facts and omits information yet it increases public engagement with the political process. However, it increases polarization and a deeper and deeper divide occurs between factions. This is bleeding into party politics and was especially obvious with Obama’s healthcare initiative.

Kelly, D. (2013). Red news, blue news: Political consequences of news bias

The news has the power to portray people of certain races, incomes or genders in certain lights. A portion of this power is in their coverage of homicides. The news coverage of homicides does, indeed, often vary by gender, race and income.

Lundman, R. J.. (2003). The Newsworthiness and Selection Bias in News about Murder: Comparative and Relative Effects of Novelty and Race and Gender Typifications on Newspaper Coverage of Homicide.Sociological Forum, 18(3), 357–386. Retrieved from http://www.jstor.org.ezproxy.lib.vt.edu/stable/3648888


The majority of participants in a web-based study share news on social media to stay connected with family and friends. They also rely on this network to guide them to news articles, since they are often similar. The backs up past research cited by the paper that news consumption is becoming a social act. Individuals under 35 are now heavily relying on their social networks for alerts to news stories.


Howe, J. (2011). Social media and news consumption (Order No. 1505751). Available from ProQuest Dissertations & Theses Global. (920121262). Retrieved from http://login.ezproxy.lib.vt.edu/login?url=http://search.proquest.com.ezproxy.lib.vt.edu/docview/920121262?accountid=14826


Current Solutions to Journalistic Issues

In order to allow for better whistle-blowing and honest reporting, the Tor Project was created. Its goal is to develop an open security toolkit to allow journalists to avoid digital surveillance by governments and other groups.



Currently it is difficult to view the comments and annotations of others. The DocumentCloud project allows individuals to crowdsource news by adding their own notes and comments to existing news material.



During big events, like the Brussels Bombing, aggregating eyewitness accounts is a complex and relatively opaque process. In order to solve this, a web-based tool, iWitness, is being created to aggregate user generated content during big events. It will then display this information for all to see.



Wikinews currently advertises itself as, “The free news source you can write!” It instructs users that they can only post things cited from reputable sources or first hand eyewitness accounts. On the news article all of the sources are listed and users have a link to edit the page. The articles are not well categorized, however, and doesn’t appear to have lots of recent content or breadth of content like traditional sources such as CNN or Fox.



Propublica states that it is an “independent, non-profit newsroom that produces investigative journalism in the public interest”. Upon browsing the site one can see that it is full of investigative journalism. However, news on breaking current events is not shown.





  • Understand the demographics of our sample
  • Usage of different mediums of news
  • Identify level of bias and filtering
  • Establish the monetary value of news
  • Find survey takers’ satisfaction with news


  1. Which sources of news do you use regularly? (check all that apply)
    1. Newspaper, magazines, or other physical periodicals
    2. Radio (e.g. NPR, talk shows)
    3. Television (e.g. local news, national cable news)
    4. News websites (e.g. Yahoo! News, CNN.com)
    5. News aggregator websites (e.g. Reddit, Google News)
    6. Social media (e.g. Facebook, Twitter)
  2. Which is your primary source of news? [Only if the responder replied to 1]
    1. Newspaper, magazines, or other physical periodicals
    2. Radio (e.g. NPR, talk shows)
    3. Television (e.g. local news, national cable news)
    4. News websites (e.g. Yahoo! News, CNN.com)
    5. News aggregator websites (e.g. Reddit, Google News)
    6. Social media (e.g. Facebook, Twitter)
  3. Satisfaction with news (Rate with stars 1-5)
    1. Quality of reporting
    2. Advertisements
    3. Entertainment
  4. How much time per day, on average, do you spend on social media?
    1. 0-1 hours
    2. 1-2 hours
    3. 3-4 hours
    4. 5+ hours
  5. What is your age?
    1. Under 18 years old
    2. 18-24 years old
    3. 25-34 years old
    4. 35-44 years old
    5. 45-54 years old
    6. 55-64 years old
    7. 65-74 years old
    8. Prefer not to answer
  6. How much would you be willing to pay to get quality news?
    1. A great deal
    2. A lot
    3. A moderate amount
    4. A little
    5. None at all
  7. How much do you currently pay to get news? Please choose the second option to verify you are paying attention.
    1. A great deal
    2. A lot
    3. A moderate amount
    4. A little
    5. None at all


We have designed this questionnaire with Qualtrics and intend to survey a random sampling of Amazon Mechanical Turk users.

We are submitting this survey by the end of this week. Our next update will include the results and analysis of our findings.

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