The Dutch election campaigns were world news….on Twitter. Political leaders of various parties discussed on RTL, a commercial broadcaster, the political problems ranging from economic issues like the government deficit to the integration of minorities. The public responded to these debates on Twitter, using the hashtag #rtldebat.Twitterati were just commenting on the debates; expressing one liners, informing others about the debates, referring to news about the debates on other media etc. The number of tweets was so big that the topic became a trending topic, reaching at his peak more than 10.000 tweets per hour. That is 3 per second. In two hours (from 20.30-22.30) 7000 persons sent 30.000 tweets. (http://twittermania.nl/2010/05/twitter-de-ban-van-premiersdebat/) The response of the politicians in this debate on Twitter was small, none of the politicians answered the tweets.
Academic research about Twitter reveals some important characteristics of the topology of the social network. The impression that the tweets are sent from a closely connected network, representing a virtual community is wrong. Participants are sending there tweets to followers. These followers could respond, re-sent the message, or send their own. But the questions is whether this process of communication represents a debate within a structured community?
1. Friends and followers
For understanding the network structure of Twitter the distinction between followers and friends is important. Friends are defined as persons who actually have responded to a tweet. It appears then that users have a very small number of friends compared to the number of followers and followees they declare. This implies the existence of two different networks: a very dense one made up of followers and followees, and a sparser
and simpler network of actual friends. The latter proves to be a more influ-
ential network in driving Twitter usage since users with many actual friends
tend to post more updates than users with few actual friends. On the other
hand, users with many followers or followees post updates more infrequently
than those with few followers or followees. Many people, including scholars, advertisers and political activists, see online social networks as an opportunity to study the propagation of ideas, the formation of social bonds and viral marketing, among others. This view should be tempered by our findings that a link between any two people does
not necessarily imply an interaction between them. That is: most of the links declared within Twitter were meaningless from an interaction point of view. Thus there is the need to find the hidden social network; the one that matters when trying to rely on word of mouth to spread an idea, a belief, or a trend in order to understand for example the political impact of Twitter. See for example: Social networks that matter: Twitter under the microscope by Huberman, Romero and Fang Wu. (http://firstmonday.org/htbin/cgiwrap/bin/ojs/index.php/fm/article/view/2317/2063)
2. Predicting the future
Twitter is not about knowledge; it is a thermometer deep into the buttocks of society; it is about the mood; popular hash tags tell us what is cool and what is hot. But if you know the mood about a certain topic, perhaps you can predict an outcome on basis of the number of tweets. This is the idea behind the study of Sitaram Asur and Bernardo Huberman, Predicting the Future with Social Media. (http://arxiv.org/abs/1003.5699) . The researchers, both working for Hewlett-Packard, analyzed in the beginning of 2009 2.89 mill tweets about 24 movies send by 1.2 mill users. A statistical analysis learned that there was a relationship between the number of tweets in the week before the movie was released and the first weekend Box-office revenues. For the horror movie The Crazies for example the statistical model predicted a revenue of 16.8 mill. The Box-office revenue was 16.06 mill. Compared to the Hollywood Stock Exchange, where people can bet on success or failure of a movie, the model performed significantly better.
After the first weekend people had actually seen the movie, and of course they twittered: they were positive or negative. Including the content of the tweets improved the model for prediction. For the second weekend the number of tweets and their content showed that positive responses improved the sales and negative responses decreased the revenue.
One could argue that the number of tweets is a measure for the interest in political issues and the elections. Therefore the number of tweets could be a predictions for the turnout of the elections, and weighing the number of tweets related to a party leader could perhaps predict the outcome of the elections.
3. Reciprocity is low
The distinction between friends and followers revealed a hidden network. This is confirmed by looking at the reciprocity. Twitter shows a low level of reciprocity; 77.9% of user pairs with any link between them are connected one-way, and only 22.1% have reciprocal relationship between them. This means that the tweets about the debate where just broadcasted, but had no follow up: opinions were only aired. No resulting in a structured debate reaching conclusions. This also confirmed from the content or character of the tweets. If one looks at Tweets following a trending topics, single tweets are most common, followed by Replies and Re-tweets.
4. Network distance between the Twitterati is short
Twitter users are all in a social network, but they separated. It could be that a user is a follower, or a follower of a follower etc. So there is distance between the Twitterati which can be measured in the number of hops needed to reach a person. In a political debate an interesting question is how far is the distance between a user and a political leader? In how many hops can a certain user of Twitter reach a specific political leader.
In social network analysis the average degree of separation is a measure connectedness. How far are Twitterati from each other? This indicates how many steps are needed for the information to reach others in the work. The outcome is astonishing short, according to research of large amounts of tweets. The 90th percentile distance, known as the effective diameter, is 4.8. For 70.5% of node pairs, the path length is 4 or shorter, and for 97.6% it is 6 or shorter. There are 1.8% users who have no incoming edge, and the longest path in our samples is 18. We note that information is to flow over less than 5 or fewer hops between 93.5% of user pairs, if it is to, taking fewer hops than on other known social networks.
See also What is Twitter, a Social Network or a News Media?
Haewoon Kwak, Changhyun Lee, Hosung Park, and Sue Moon
Proceedings of the 19th International World Wide Web (WWW) Conference, April 26-30, 2010, Raleigh NC (USA)
5. Geography and popularity
A social network on Twitter could physically be very extended. Internet has no borders and Twitterati could be in various parts of the world. But looking at the hidden network of friends, that is looking from reciprocity, the international dimension is quite limited. Research shows that Twitter users who have reciprocal relations of fewer than 2, 000 are likely to be geographically close. Users with followers 1, 000 or less are likely to be geographically close to their r-friends and also have similar popularity with their r-friends. So average Twitter users are in the same geographical space Secondly they have the same status on Twitter, generally they have the same numbers of followers and the sent the same number of tweets.
6. Spreading information or social networking
Twitter can be viewed fro two different perspectives. Either Twitter is used for spreading information. That is ending a message to others and informing them, or it is a way to build a relationship. Facebook is an example of the last one. Twitter is an example of the former. The act of following as subscribing to tweets, serves more as an information spreading medium than an on line social networking service. Twitter is therefore less used for maintaining social contacts, connecting to friends, then for spreading and sharing information. Twitter is in the first place an information service and not a social networking tool, because the reciprocity is low.
7. Twitter is about news
Journalists have discovered Twitter as an interesting news source, especially in cases where the news develops so fats that the main stream networks cannot cover the development of the news. Twitter is therefore an interesting source for breaking news. This is sustained by the finding that Twitter is about spreading of information and not about social networking. Secondly research reveal that trending topics on Twitter are related to for example headlines. Twitter is more a media for breaking news. Comparing trending topics on Twitter with Google trend and with CNN headlines, the conclusion was that trending topics followed more headlines than the Google trend. Only 3% of the trending topics on Twitter are represented in Google Trend. Half of the time Twitter trend followed CNN Headlines. Some news broke out on Twitter before CNN and they were on live broadcasting nature such as sports events or accidents.
8. Trending topics last shorter then a week
News comes and goes like the tide. If Twitter is news service it should also have a news cycle. And the questions is how long lives news on Twitter? What is the average life time of a Twitter trend. About 15% of topics have 2 active periods and 5% have 3. Very few have more than 3 active periods. Most of the active periods are a week or shorter. 31% Of periods are 1 day long, and only 7% of periods are longer than 10 days. Concluding therefore that Twitter users tend to talk about topics from headline news and respond to fresh news.
9. Power of re-tweeting
Although single tweets are most common, re-tweets have a special power. The mechanism of retweet has given every user the power to spread information broadly. Retweets reach a good number of people no matter many followers the tweet source has.
The influentials by the number of retweets are dissimilar with those by the number of followers. Individual users have the power to dictate which information is important and should spread by the form of retweet, which collectively determines the importance of the original tweet.
