Twitter – My CMS

Conversation practices and network structure in Twitter – SIGSNA paper at ICWSM12

Our paper Conversation practices and network structure in Twitter has been accepted as poster paper for the upcoming International AAAI Conference on Weblogs and Social Media (ICWSM12) that will be held in Dublin in June. We are really happy to be part of the conference of many reasons. On one side ICWSM is an interesting venue where researchers coming both from the computer sciences and from the social sciences have the opportunity to come together presenting their own researches and approaches. As we know from our personal experience that is not an easy dialogue but it is really valuable.
At the same time we are really happy about our paper Conversation practices and network structure in Twitter that deals with an intriguing and still largely unexplored aspect of Twitter: if and why the participation to hashtag conversation leads to the acquisition of new followers. While the topic might seem very specific it might be a first step toward the construction of connections between those researches based on the analysis of hashtag-based conversation and those based on the analysis of following network.
We are going to publish – as usual – a preprin version of the paper as soon as possible.Our paper Conversation practices and network structure in Twitter has been accepted as poster paper for the upcoming International AAAI Conference on Weblogs and Social Media (ICWSM12) that will be held in Dublin in June. We are really happy to be part of the conference of many reasons. On one side ICWSM is an interesting venue where researchers coming both from the computer sciences and from the social sciences have the opportunity to come together presenting their own researches and approaches. As we know from our personal experience that is not an easy dialogue but it is really valuable.
At the same time we are really happy about our paper Conversation practices and network structure in Twitter that deals with an intriguing and still largely unexplored aspect of Twitter: if and why the participation to hashtag conversation leads to the acquisition of new followers. While the topic might seem very specific it might be a first step toward the construction of connections between those researches based on the analysis of hashtag-based conversation and those based on the analysis of following network.
We are going to publish – as usual – a preprin version of the paper as soon as possible.

Upcoming conferences and activities

After some quite time we can now update the list of the upcoming event and presentations. March will be a busy period with a major conference and two very interesting workshops where we are going to presents the new research lines we’re carrying on this year. Between the 12th and the 18th of March we are going to attend the XXXII Sunbelt conference at Redondo Beach, CA. During the conference we’re presenting some new empirical data about on the Multy-Layer Model for SNS analysis.
As soon as we’ll be back in Europe we will attend the 2nd Düsseldorf Workshop on Interdisciplinary Approaches to Twitter Analysis (#diata12) where we will introduce our new research aimed at understanding how the Twitter network structure evolves according to the social interaction that takes place between the users (we hope to be able to post more about this really soon).
After some quite time we can now update the list of the upcoming event and presentations. March will be a busy period with a major conference and two very interesting workshops where we are going to presents the new research lines we’re carrying on this year. Between the 12th and the 18th of March we are going to attend the XXXII Sunbelt conference at Redondo Beach, CA. During the conference we’re presenting some new empirical data about on the Multy-Layer Model for SNS analysis.
As soon as we’ll be back in Europe we will attend the 2nd Düsseldorf Workshop on Interdisciplinary Approaches to Twitter Analysis (#diata12) where we will introduce our new research aimed at understanding how the Twitter network structure evolves according to the social interaction that takes place between the users (we hope to be able to post more about this really soon).

What if Twitter wasn't the fastest one…

[Italiano] We have recently done some comparative analysis between Twitter propagation dynamics and FriendFeed propagation dynamics. We chose, as our case study, the news related to the rescue operations of the San Josè mining accident (that left 33 men trapped 700 metres (2,300 ft) below ground for 69 days) [I’m not describing the research now, we have a paper under submission.. so stay tuned for more about the research itself].
As a side product of this research we had the opportunity to monitor the audience exposed to the miner’s rescue news both on Friendfeed and on Twitter. We were therefore able to observe how fast a specific news spreaded through both the networsk and, since we are observing the same news, we can assume that different propagation speeds can be related to the different propagation mechanisms taking place into the two systems.
Even considering the huge difference in absolute numbers (Twitter has a larger number of users) the line of FriendFeed based propagation (Esposti FF) is steeper and shows a less linear progression than Twitter’s line (Esposti TW).

This seems to suggest that a propagation based largely on the interactions made by the people you follow is faster than a propagation based mostly on explicit re-sharing practices (ReTweets).[English]

Come effetto collaterale di una ricerca che abbiamo da poco concluso sulla propagazione online delle news relative al salvataggio dei minatori chileni intrappolati nella miniera di San Jose abbiamo potuto verificare la velocità di propagazione di una notizia all’interno del network di Friendfeed e di Twitter. Dato che la notizia di partenza era la stessa possiamo ipotizzare che le differenze di propagazione osservate siano imputabili ai meccanismi di propagazione dei due sitstemi. Anche tenendo in considerazione l’enorme differenza in termini numerici la curva della propagazione di FriendFeed appare molto più ripida e meno lineare di quella di Twitter.

Questa differenza sembrerebbe indicare come un meccanismo di propagazine basato sulle interazioni dei propri contatti (come avviene su FriendFeed) piuttosto che su esplicite pratiche di propagazione risulti essere più efficace dal punto di vista della velocità.