In this class activity we will use TwitterTrails (http://twittertrails.com/) to analyze the origin, spread, and validity of a “story” on Twitter (a claim, a meme or an event). Prompted by a search with relevant keywords using the Twitter API, TwitterTrails collects and analyzes up to 200K tweets automatically. While it does not answer directly the question of a story’s validity, it provides information that a critically thinking person can use to examine how Twitter users reacted to the spreading of the story.

Here is an example describing the use of TwitterTrails for investigating a story about Plane in the Sea Near Canary Islands:

Team member names:
STEP 1: Propagation Graph
The Propagation Graph highlights the tweets which were influential in breaking the story on Twitter, and highlights independent content creators. Each point on the graph represents a tweet, and hovering over or clicking on the point will display the tweet to the right of the graph.

Tweets are plotted on x-axis of the graph based on the time they were posted, and on the y-axis by the number of retweets they have received (at the time of data collection).

Color (if other than the default gray) = similarity in wording used; tweets with nearly identical texts will have points that are the same color
Size = logarithmic of potential to be viewed (number of followers)
Blue border = tweets written by verified accounts

What is the range and unit on the x-axis?
What is the range and unit on the y-axis?
Which tweet do you consider responsible for breaking the story?
When did the story break? *
Are there any tweets in the propagation graph that are not related to the story?
STEP 2: Time Series of Relevant Tweets
This graph shows the activity over time of relevant data we collected, and the estimated total activity of that data (based on the number of retweets of the tweets we collected). Time is on the x-axis and the number of tweets generated is on the y-axis. Each point represents a ten minute time span. You can zoom in on the graph by clicking and dragging your mouse over a period of time.

Clicking on "Manage Series" on the bottom right of the display will open a panel which you can use to add new time series to the graph by checking the box on the left. The Search function takes a search term in the text box, and will display all tweets contain (the exact) search term when you check the box on the left of Search.

Selecting a point on the graph will display the tweets from that series in that ten minute time span to the right of the graph. These tweets are sorted by the number of retweets they have received (highest on top), and can be re-sorted using the drop down menus. If there are more than 50 tweets in the time span, links to navigate the tweets 50 at a time are provided.

What was the maximum number of tweets at any point during the timeline? At what time it reached that maximum?
When was the first relevant tweet sent?
What was the time between the first tweet and the tweet that broke the story? *
Do you observe anything unusual about the shape of the time series?
STEP 3: Co-retweeted Network
This graph explores how the people that tweet about this story are connected by showing the network of co-retweeeted users in the data. The co-retweeted network highlights influential accounts in the retweet network, by connecting accounts based on mutual retweeting users. That is, if User A and User B in the co-retweeted network are connected by an edge, it means at least one other user has retweeted User A and retweeted User B.

Hovering over a point will display the name of the user it represents, and clicking on it will bring up information about the user on the right of the graph. The user information also contains the tweets written/retweeted by that user in the dataset..

Focus on the major groups (the ones that have significantly more nodes than the rest).
Explore this graph and click on the keywords from each major group to investigate further.

- Colors correspond to groups
- Only one group = echo chamber
- Well-separated groups = polarization

How many major groups do you observe in this graph?
What are the characteristics of these groups?
Can you identify a general profile for each major group?
Do you observe any polarization? What do you think is the source of any polarization?
STEP 4: Pictures
The most retweeted images about the story are displayed in this visualization. Hovering over an image will open the tweet on Twitter in which that image was posted.
Look at the pictures related to the story, how can you describe them?
STEP 5: Tags
From the following lists of tags, select any that apply to the story.
Co-RTed Graph Shape: Based the co-retweeted graph, which of the following terms describe its polarization?
Co-RTed Graph Composition: Based on the self-description words of the group members, which of the following terms describe the story?
Give three keywords that you think describe the story