Visualizing the world's Twitter data - Jer Thorp

TED-Ed
21 Feb 201305:41
EducationalLearning
32 Likes 10 Comments

TLDRThe speaker, charmed by the politeness on Twitter, created a program to map 'Good morning' tweets worldwide, revealing patterns in global wake-up times. He expanded this idea to track travel patterns from tweets about landing in various locations, offering valuable insights for scientists studying disease spread. The speaker's work at the New York Times involves modeling conversation dynamics around articles, creating interactive, exploratory tools. He advocates for individuals to take control of their data to collectively tackle global challenges, emphasizing the power of big data in problem-solving.

Takeaways
  • 🌐 The speaker was charmed by the politeness on Twitter, with people greeting each other with 'Good morning!'
  • 📊 The speaker created a program to record and visualize the global pattern of 'Good morning!' tweets, revealing different waking habits across the world.
  • 🌍 The visualization showed that people on the West Coast wake up later compared to those on the East Coast.
  • 🛫 People often share their travel updates on Twitter, such as landing in various locations, which can be seen as a form of showing off.
  • 🔍 By mapping these travel tweets, the speaker created a model of global travel patterns, which could be useful for scientists studying disease spread.
  • 🏢 The speaker works at the New York Times and has been involved in a project called 'Cascade', modeling how people talk and discuss topics.
  • 💬 'Cascade' allows for the analysis of discussions around specific articles, showing the scope and spread of conversations over time.
  • 📈 The project provides a three-dimensional view of conversations, which is more intuitive for humans to understand and analyze.
  • 🔎 The New York Times uses this tool to model conversations around their content, revealing different conversational architectures based on the story and its reach.
  • 💡 The speaker emphasizes the value of small data pieces when combined, suggesting that collective data can be used to solve big problems.
  • 🌟 The speaker advocates for individuals to take control of their own data, as it is a valuable resource that can be used to tackle some of the world's most challenging issues.
Q & A

  • What initially charmed the speaker about Twitter?

    -The speaker was charmed by the politeness of people on Twitter who would greet each other with 'Good morning!' as they woke up.

  • How did the speaker utilize the 'Good morning!' greetings on Twitter?

    -The speaker wrote a computer program to record 24 hours of 'Good morning!' greetings on Twitter, creating a visual representation of the wave of greetings across the world as people woke up at different times.

  • What can the map of 'Good morning!' greetings tell us about people's waking habits around the world?

    -The map can show us that people on the West Coast wake up later than those on the East Coast, indicating differences in waking habits across various regions.

  • What is the significance of the tweets about people's travel locations?

    -While these tweets may seem like simple updates about travel, they actually provide valuable data about people's movements, which can be useful for various applications, including scientific research on disease spread.

  • How did the speaker turn the vanity of Twitter users into utility?

    -The speaker mapped the travel data from tweets about people's locations, combining it with information from their Twitter profiles to create a model of global travel patterns over a 36-hour period.

  • What is the 'Cascade' project at the New York Times?

    -The 'Cascade' project is an initiative that models how people talk on social media, specifically focusing on the structure and spread of discussions around articles and other content.

  • How does the three-dimensional view of conversations provide additional insights?

    -The three-dimensional view allows for a more human-like understanding of the conversations, making it easier to see the off-shoots and the progression of discussions, which can be very useful for analyzing the scope and impact of conversations.

  • What is the speaker's suggestion regarding the storage of our personal data?

    -The speaker suggests that instead of trusting companies to store our data, we should take control of our own data because we are the ones who generate and own it.

  • What is the potential of big data according to the speaker?

    -The speaker believes that big data has the potential to solve big problems, especially when it is collectively used and controlled by everyone who generates it.

  • How does the speaker's work contribute to understanding social media dynamics?

    -The speaker's work involves analyzing and visualizing data from social media platforms like Twitter to understand patterns of communication, movement, and behavior, which can provide valuable insights for various fields, including journalism and scientific research.

  • What are 'conversational architectures' and how do they vary?

    -Conversational architectures refer to the visual structures that represent the flow and spread of discussions on social media. They vary depending on the story, the speed at which people talk about it, and how far the conversation spreads.

Outlines
00:00
🌐 Mapping Global Greetings on Twitter

The speaker, a Canadian and self-proclaimed nerd, shares his fascination with the politeness displayed on Twitter through morning greetings. He created a program to record and visualize 24 hours of 'Good morning!' tweets from around the world. The visualization shows different colors representing the time people wake up and greet, with green for 8 AM, orange for 9 AM, and red for 10 AM. The speaker notes that West Coast residents wake up later than their East Coast counterparts. He further discusses how people share their travel updates on Twitter, which he refers to as 'show-offs', and how he mapped these travel patterns to create a model of global travel in 36 hours. This model is useful for scientists studying disease spread. The speaker works at the New York Times and has been involved in a project called 'Cascade', which models how people talk and discuss topics on social media, providing a detailed view of conversations over time and in three dimensions. The speaker emphasizes the value of small data pieces when put together and the potential for collective data use to solve big problems.

05:00
💡 Empowering Individuals with Their Data

The speaker transitions from discussing Twitter data to the broader concept of personal data ownership. He emphasizes that every individual is a data-producing machine and that the data measured about a person belongs to them. He advocates for a collective approach to using this valuable data to tackle the world's most challenging problems. The speaker, possibly influenced by his Canadian roots, hopes that people will come together to use their data for the greater good, under their control rather than relying on companies to store and use their data. He concludes with a call to action for individuals to take ownership of their data and use it to make a positive impact.

Mindmap
Keywords
💡Twitter
Twitter is a social media platform where users post and interact with messages known as 'tweets'. In the context of the video, Twitter is used as a source of data to study human behavior, such as morning greetings and travel patterns. The speaker uses Twitter as an example to show how seemingly trivial messages can be aggregated to reveal interesting patterns and insights about people's lives and habits.
💡Politeness
Politeness refers to the expression of manners and respectful behavior in social interactions. In the video, the speaker is charmed by the politeness exhibited on Twitter through morning greetings, which is seen as a cultural norm and a positive aspect of online communication.
💡Data
Data refers to pieces of information or facts that are collected and can be analyzed to reveal patterns or draw conclusions. In the video, the speaker discusses how data from social media, like Twitter, can be used to understand human behavior, such as waking up habits and travel movements.
💡Vanity
Vanity, in the context of the video, refers to the tendency of individuals to share personal achievements or experiences online to gain attention or admiration from others. The speaker uses this concept to describe how people share their travel experiences on Twitter, which can be seen as a form of showing off.
💡Utility
Utility refers to the practical use or value of something. In the video, the speaker discusses how the vanity exhibited on Twitter can be transformed into utility by using the data from people's tweets to create models and gain insights into human behavior and movement patterns.
💡Modeling
Modeling in this context refers to the process of creating a representation or simulation of a real-world phenomenon based on data. The speaker uses data from social media to model human behavior, such as how people wake up around the world and how discussions unfold on social media platforms.
💡Social Media
Social media refers to websites and applications that enable users to create and share content or participate in social networking. In the video, social media platforms like Twitter and Facebook are discussed as sources of data that can be analyzed to understand human behavior and communication patterns.
💡Cascade
Cascade, as mentioned in the video, is a project by the New York Times that models how people talk and discuss topics on social media. It aims to visualize and analyze the spread and structure of conversations around specific content, such as articles.
💡Conversational Architectures
Conversational Architectures, as used in the video, refers to the visual and structural representations of how discussions unfold on social media. These architectures can take different forms depending on the nature of the conversation, the story being discussed, and the level of engagement from the participants.
💡Big Data
Big Data refers to the large and complex sets of data that can be analyzed to reveal patterns, trends, and associations, especially relating to human behavior and interactions. In the video, the speaker emphasizes the potential of big data to solve significant problems by harnessing the collective data generated by individuals.
💡Data Ownership
Data ownership pertains to the concept of individuals having control over their personal data, including the right to store, use, and share it as they see fit. The speaker argues that rather than entrusting companies with our data, we should take ownership of it, recognizing its value and potential for addressing global issues.
Highlights

The speaker began using Twitter a couple of years ago and was charmed by the politeness of people greeting each other with 'Good morning!'

As a Canadian, the speaker appreciated the politeness on Twitter.

The speaker's interest in programming led to the creation of a program that recorded 24 hours of 'Good morning!' greetings on Twitter.

The visualization of 'Good morning!' greetings showed a wave of people waking up at different times across the world.

People on the West Coast wake up later than those on the East Coast, as observed from the 'Good morning!' data.

The speaker also mapped people's travel patterns based on their tweets about landing in various locations.

The mapped travel data created from Twitter can be a useful resource for scientists studying disease spread.

The speaker works at the New York Times and has been involved in a project called 'Cascade', modeling how people talk.

The 'Cascade' project visualizes discussions around articles, such as 'The Island Where People Forget to Die'.

Conversations can be viewed in a three-dimensional format, which is more intuitive for humans.

The New York Times uses an interactive, exploratory tool to model the conversations around their content.

Different stories and conversation speeds result in unique 'conversational architectures'.

The speaker suggests that we are all data-making machines and produce data constantly.

The speaker proposes that instead of trusting companies with our data, we should take control of it ourselves.

The idea is to collectively use our data to tackle the world's most difficult problems.

Big data has the potential to solve big problems most effectively when controlled by everyone.

The speaker ends with a hopeful note, encouraging collective action and data ownership.

Transcripts

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SocialDataGlobalPatternsDiseaseModelingTwitterAnalysisDataVanityPersonalDataBigDataSolutionsDataOwnershipSocialMediaInsightsCascadeProject