New York Times Innovation Portfolio

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posted by Zeke Shore on Mar 2nd, 2010

nyt_innovation

The New York Times online consistently delivers interesting data visualizations to help enrich the stories surrounding popular news topics. The New York Times Innovation Portfolio provides a beautiful overview of all of these interactive explorations, organized by topic with project overviews, documention, and links to the actual interactive pieces.

Since VoxPop is working with New York Times data, this collection of existing data visualizations is a treasure trove of strong precedents, several of which relate very closely to our project. Here are a handful that live within the realm of reader sentiment.

Health Care Debate

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Health Care Debate is a conversation platform that allows users to discuss various issues within the health care debate. The most interesting aspect of this tool is how the relevance of specific sub-topics within the debate can be instantly comprehended at first glance, with the surface of the tool depicting multiple “rooms” that are scaled relative to the number comments relating to that subtopic.

Obama’s Address In Cairo

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This interactive video of Obama’s speech to the Muslim world allows users to provide comments along the timeline of the speech, allowing a global discussion to unfold in the context of the time-based content that is seeding the discussion.

Election Word Train

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Election Word Train asked New York times readers to share one word that describes their current state of mind on the day of the 2008 presidential election. Much like a tag cloud, words are scaled relative to the number of people sharing the sentiment, and can be filtered to show words shared by Obama or McCain supporters. By leveraging scale and letting these words ’speak for themselves’ does effectively provide a general glimpse of reader sentiment, even if the forum is is somewhat contrived, specifically with the goal reducing group sentiment into a few dozen words, possibly hindering truly organic sentiment visualization.

Inaugural Words

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Inaugural Words ranks the frequency of words used by presidents in Inaugural Addresses, showing what words each president used the most. While is not really reflecting reader sentiment. it does show an interesting break down of word frequency across time and political position.

Twitter Bowl

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The Twitter Bowl interactive visualization maps twitter chatter over the course of the 2009 Super Bowl, according to key topic mentions. This hits an interesting cross section of communicating time, space, and group sentiment, even if it is somewhat cryptic in what is actually being communicated. There is something very satisfying about seeing topics grow and shrink geographically over time, although it does not reveal what specifically about “steelers” or “ads” or “springsteen” people are sharing.

These projects all have several aspects that worth analyzing and building upon. As we begin to re-think how people engage with the news, its exciting to see major players like the New York Times continuing to push the envelope, and continue to keep their data open so that others can do the same.

Visualizing NYT Discourse – Design Iteration 3

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posted by Zeke Shore on Mar 1st, 2010

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The last design iteration I wrote about a couple weeks ago started to take a departure from earlier iterations by exploring the idea of representing the personality of every comment on the New York Times website (that relates to any given topic) as it’s own entity, and visually describing it’s sentiment or personality.

After reflecting back on our original reasons for wanting to visualize online discussions, our thesis question really centers around how can the ‘Vox Populi‘ still be heard as reader participation in the journalistic process scales to hundreds of thousands of comments spread across hundreds of articles and blog posts for even just one news source.

So this resulted in a design prototype that involved rendering comments for a given topic as balls swarming around the article that seeded the conversation, representing sentiment with color, opacity, and speed of movement, describing each comment’s polarity (how positive or negative), strength (strong or weak) and activity (active or passive) respectively.

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While this iteration was both readable and interesting to look at, it suffered in terms of scalability. We could realistically only look at a couple conversations at a time for any given topic. So the next phase of the design process involved trying pull some of the more successful aspects of this iteration into a more real estate friendly composition. The logical progression of this involved breaking conversation into a linear organization (all of the following mock ups are not visualizing real data, but rather serving as design explorations).

v1.5.2

Of course horizontal flows of information are rarely web-friendly, despite it being a logical way to organize content chronologically. So this quickly evolved into a vertical orientation, and opened the door for exploring the concept of possibly showing when commenters reference each other within a conversation.

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