Part 1
Tweet-o-Meter, a simply displayed twitter tool site that measures the amount of tweets across the globe per minute. Tweet-o-Meter’s design purpose was to scour online data for later analysis of social and temporal dynamics within the Twitter demographic. Developed by CASA, University College London as a part of the National e-Infrastructure for Social Simulation who provide a platform for social scientists and their produced powerful simulation tools.
Tweet-o-Meter has been used as a tool for 21st century media professionals, and can be continually used. Some examples of this twitter tool being used as a part of 21st century media production and/or the uses of the tool are provided:
1. http://mashable.com/2011/03/11/japan-tsunami/
Twitter Users React To Massive Quake, Tsunami In Japan (Taylor, 2011):
An article on a social media site itself covering the natural disasters that shook Japan in 2011, with the author (a journalist of 15 years) using Tweet-o-Meter to display the powerful use of Twitter as a communication tool during the situation. The Tweet-o-Meter showing a clear display of the vast rise in tweets from Japan in comparison to other cities of the world displayed.
Tweet-o-Meter on CNN (Gray, 2011):
A amateur video (uploaded by the creator of Tweet-o-Meter, Steven Gray) of the CNN television news report on social media’s significant role throughout the Japan earthquake and tsunami, incorporating Tweet-o-Meter into the analysis of social media as a lifeline during disasters, showing the vast amount of tweets per minute calculated by the Tweet-o-Meter during the natural disasters in Japan.
3. http://www.wired.co.uk/news/archive/2010-01/29/meet-neiss-and-the-tweet-o-meter.aspx
Meet neISS and the Tweet-o-Meter (Brown, 2010):
A laid back article introducing Tweet-o-Meter and its basic functions. Includes a description of various setbacks to the tool such as its reliance on a niche of users (in some cities) and an array of timezones. Almost taking a subtly cynical stance on the tool, questioning its validity in “understanding social and temporal dynamics”.
4. http://www.digitalurban.org/2010/10/real-life-tweet-o-meters-now-in-british.html
Real Life Tweet-o-Meters Now in the British Library (Andy, 2010):
A short article on the production of physical Tweet-o-Meters put for display to visitors of the British Library. An article describing the functions of the new analogue Tweet-o-Meters and their comparative features to the online digital social media analysis tool.
5. http://bbh-labs.com/mapping-twitter-part-2-the-tweet-o-meter
Mapping Twitter Part 2: The Tweet-o-Meter (Malbon, 2010):
A basic introduction to Tweet-o-Meter and its future possibilities. Majorly pro Tweet-o-Meter, the article refers to functions the social media analysis tool is undergoing for future studies and data analysis (ie. gathered twitter information over time to show twitter activity over time and space).
The ins and outs of using and exploring Tweet-o-Meter:
Tweet-o-Meter is a very simple digital device, lacking complexity and links within links on its site that many social media sites contain. As the tool is a part of the CASA, University College London NeISS (National e-Infrastructure for Social Stimulation) program, it doesn’t sit on its own website, but rather is an extension of the CASA, University College London home website.
Figure 1. Tweet-o-Meter URL.
Tweet-o-Meter’s home page contains the majority of the entirety of the site.
Figure 2. Main section, top of Tweet-o-Meter’s homepage/site.
The top and main section of the site (as shown in Figure 2) displays simply twelve cities ranging from the US to cities in Europe to Tokyo, lone-standingly representing Asia. As seen in Figure 2, twelve cities’ tweets per minute (Figure 3) are represented by individual gauges, updated every couple of seconds, you can analyse live which cities are the most active on twitter in that instance.
Figure 3. Tweets measurement, bottom line of website.
Figure 4. Live Tweets from New York, London, Paris and Munich.
As seen in Figure 4, scrolling down the homepage of the site shows a section devoted to live tweets. displayed from New York, London, Paris and Munich. The tweets are refreshed constantly every few seconds.
At the bottom boxed off section of the homepage, two other tabs can also be seen (Top of Figure 4):- ‘Graphs’ and ‘About’.
Figure 5. ‘Graphs’ tab.
When clicking on the next tab over, ‘Graphs’ (Figure 5), nothing is displayed nor is any information provided as to the missing section. Presumably, it may have once displayed an analysis of some sort, as various media sites have alluded to the site doing (as seen in the hyperlinks discussed in the beginning of this report), but currently does not provide any beneficial uses for a modern day communications professional looking to use the tool.
Figure 6. ‘About’ tab.
The ‘About’ tab, like the website, is simply put and an informal, relaxed introduction to the purpose of the site/tool.
Affordances and Constraints of using Tweet-o-Meter:
Ian Hutchby (2001), described a technological affordance to be ‘functional and relational aspects which frame, while not determining, the possibilities for agentic action in relation to an object’. Tweet-o-Meter as a digital tool has it’s affordances and constraints as a technology.
Twitter contains an enormous number of text posts and it grows every day. The collected corpus can be arbitrarily large (Pak & Paroubek, 2010). The enormity of twitter is a constraint in that there is such a vast amount of information to be analysed. This constraint can also be positive though, as it has such a large bank of data that can be observed and measured.
Twitter’s audience is represented by users from many countries. Although users from U.S. are prevailing, it is possible to collect data in different languages (Pak & Paroubek, 2010).
Similar to the constraint of twitter’s enormity, another constraint to the measuring of data given in tweets are language barriers. As twitter is available to a range of countries with a range of languages people tweet in. This can cause problems when trying to collect a range of information when certain topics being analysed are in different languages where a direct translation may not have the same meaning or where slang is used in different instances, especially on an informal social media platform.
Technically, the twitter tool has its physical allowances and limits such as the site itself, not extending to other pages, adding to the simplicity of the tool. Another limit would be the city gauges displaying tweets per minute in each respective city; all tools have a maximum of 1200 tweets per minute. This is a constraint in the tool as it doesn’t allow for a great amount of tweets to be shown past 1200 per minute. Though, it can also be considered a positive aspect to the tool as it allows for a consistent measurement of each city comparatively.
The city gauges are also dependent on time zones. This makes it hard to analyse and compare cities against each other when tweets per minute are analyse against each other at different times of the day for different cities. Another constraint to the tool would be the limited cities measured, only 16 of the world when there are many other major cities that 21st century media professionals would be interested in viewing.
The tool itself also only allows for live updates to be seen, there’s no way to view archives of analysed information as the graphs section (figure 5) which supposedly would show analysis of tweets and trends is not functioning. The live tweets shown (figure 4) also only include four cities for the world: New York, London, Paris, Munich. These tweets also include personal tweets, and is not limited to direct tweets tweeted into the social media. This can constrain a media professionals analysis of the live tweets as the space could be crowded by jargon, but it could also be viewed as a positive section honed in and focused on a select few cities.
Pros and Cons of using Tweet-o-Meter as a tool in 21st century professional media research:
| Research/Presentation Tasks | Pro | Con | N/A |
| Selecting a topic | |||
| Media Research* | The ability to view volumes of tweets in a simple fashion, simply laid out. Makes easy for professional communicators to analyse. | Very simple tool, can create limited information gain, not allowing for much in depth analysis into twitter trends, especially as the ‘graphs’ section is no longer in use (figure 5) | |
| Newsworthiness* | Ability to used in news stories that incorporate the significance of social media (or specifically twitter), such as during the Japan natural disasters (hyperlinks in the beginning of the report) | Doesn’t hold much relevance to media that don’t incorporate social media within their stories. Social media analysis can also be skewered and rely heavily on a niche of people’s opinions. | |
| Angle* | If social media plays a major part in a story, Tweet-o-Meter would be a great tool to use to help analyse that and give effect to the story. | Limited story angles that can be provided from Tweet-o-Meter. Tool only provides a social media angle and limited analysis of that social media (figure 4, live tweets) | |
| Defining topic* | X | ||
| Choosing sources* | Sources are only provided via social media. | ||
| Gathering information | |||
| Facts and figures* | X (missing graphs section which may have provided this analysis information -figure 5) | ||
| Interviews* | X | ||
| Anecdotes* | X | ||
| Documents* | X | ||
| Photographs* | Photos can only be accessed via links on the live tweet section (figure 4), would not be individually shown on site. And most would not be relevant to analysis. | ||
| Video | Same as photographs (above) | ||
| Audio | Same as audio (above) | X (rarely find audio, unless it’s attached to a tweet) | |
| Data Analysis | |||
| Checking credibility* | Doesn’t allow for sources of information provided on tweets. | ||
| Selecting most important data* | Difficult as the only provided information is refreshed every couple of seconds, eg. amount of tweets per minute or the live tweets shown. | ||
| Writing the article | |||
| Pyramid structure* | X | ||
| Flow/clearness* | X | ||
| Spelling/Grammar/Punctuation | Information provide (live tweets, figure 4) are public opinion and are not under a set of grammatical or structural rules. | ||
| Presentation | |||
| Designing layout* | Very simply set out and easy to view/analyse. | ||
| Publishing | |||
| Audience reach | X | ||
| Accessibility | Online, easy to reach for 21st century media professionals. | Doesn’t have its own domain name, but not a major flaw. | |
*(Ricketson 2004, pp.95-186; Spencer 2006, pp.25-122)
References
Taylor, C. (2011). Twitter Users React To Massive Quake, Tsunami In Japan. Retrieved August 31, 2012, from http://mashable.com/2011/03/11/japan-tsunami/
Gray, S. (2011). Tweet-o-Meter on CNN. Retrieved August 31, 2012, from https://vimeo.com/20959622
Brown, M. (2010). Meet neISS and the Tweet-o-Meter. Retrieved August 31, 2012, from http://www.wired.co.uk/news/archive/2010-01/29/meet-neiss-and-the-tweet-o-meter.aspx
Andy. (2010). Real Life Tweet-o-Meters Now in the British Library. Retrieved August 31, 2012, from http://www.digitalurban.org/2010/10/real-life-tweet-o-meters-now-in-british.html
Malbon, B. (2010). Mapping Twitter Part 2: The Tweet-o-Meter. Retrieved August 31, 2012, from http://bbh-labs.com/mapping-twitter-part-2-the-tweet-o-meter
Hutchby, I. (2001). Technologies, Texts and Affordances. Sociology, 35(2), 441-456.
Pak, A. & Paroubek, P. (2010). Twitter as a Corpus for Sentiment Analysis and Opinion Mining. Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10). Valletta, Malta: European Language Resources Association.
Part 2
The First Lady’s Speech Sends Twitter Discussion Wild
Pictured above: Michelle Obama speaking at the Democratic convention. Photo obtained by Fox News.
Michelle Obama opened her husband’s campaign for a second term in office by delivering a powerful speech on the first night of the Democratic National Convention.
Obama defended her husband’s character and decisions in his term in office.
“When it comes to the health of our families, Barack refused to listen to all those folks who told him to leave health reform for another day, another president,” she said. “He didn’t care whether it was the easy thing to do politically. No, that’s not how he was raised. He cared that it was the right thing to do.”
The first lady defended her husband and all those who had trusted him in the 2008 election to continue trusting him now.
“He reminds me that we are playing a long game here, and that change is hard, and change is slow, and it never happens all at once. But eventually we get there, we always do,” she said.
The public took to twitter to share their thoughts on her speech. Amongst the many speakers at the convention, Michelle Obama’s name was the one that continued to arise in twitter discussions. In the United States, she rose to be a trending topic on twitter. All the way in Australia, she continued to rise high in twitter discussions topping the trending topics list.
Twitter hashtags such as #michelleobama, or her name ‘Michelle Obama’ or also, #DNC2012 and #DNC trended worldwide whilst she gave her speech and for hours after.
Tweet measuring tools such as, Tweet-o-Meter, were also able to capture the amount of tweeting underway in cities within the United States. 
New York city tweet gauge well and truly at it’s maximum. Photo obtained by screenshot of Tweet-o-Meter site.
The social media measuring tool, Tweet-o-Meter, showed New York’s tweet limit to be at it’s very limit, at least 1200 tweets per minute, where Michelle Obama, #michelleobama, #DNC2012 were all trending on twitter.
The first lady’s speech was said to be soft in tone yet strong in belief after speakers such as Senate Majority Leader Harry Reid, Newark (N.J.) Mayor Cory Booker and of course, Mitt Romney.
“The guy who’d picked me up for our dates in a car that was so rusted out, I could actually see the pavement going by through a hole in the passenger side door … the guy whose proudest possession was a coffee table he’d found in a dumpster, and whose only pair of decent shoes was half a size too small,” she said.