Big Data and Social Mining


n october 9, I attended a live seminar about Big Data and Social Mining, organized by PMI-NIC (PMI Northern Italy Chapter) in Milan.

The organizer, professor Francesco Varanini, on his blog – – writes that

“… every project leaves digital traces … created and maintained by digital devices …”

and he continues ” … Big Data are just this: a big mass of data, initially served to a precise aim, but above all useful to the project’s government …”

and about the project team’s he states “… the real challenge is to understand how in the digital material organized by the project team are hidden unexpected knowledge …”

I found very interesting two speeches, the first held by two university researchers (University of Pisa) Simone Ferrucci and Emmanuele Chersoni and the second held by a very experienced TrentoRISE researcher Marco Guerini.

Cytoscape Network Visualization Example

Cytoscape Network Example

Simone Ferrucci and Emmanuele Chersoni showed an interesting application; they explained how simple was to build the network of relations among the followers of a particular subject on Twitter. For that aim they used Cytoscape – – an interesting Open source bioinformatics software platform for visualizing molecular interaction networks.

Though its original scope was different, you could use it for building a network based, for example, on the stakeholders of a project through the analysis of all the emails shared during the entire life of the initiative.

But what are we supposed to do with the result of this analysis? We could become aware of a distorsion in the communication lines and we could take corrective actions.

Another very interesting speech was held by Marco Guerini (TrentoRISE); he analyzed many US political speeches with reference to the behavior and intentions of the speaker.

Social Mining

Social Data Mining

He mentioned the negative and positive buzzes caused by the speaker’s behavior (or intentions); analyzing the comments to their speeches as well as the reactions, he could find some very interesting differences, for example, between male and female politicians (for example female are less aggressive and use less negative terms than male politicians to attract consensus).

Comparing this research to project management activities, the PM could analyze the content of his/her emails collected during the whole life of the project discovering unexpected relations and behavior that could bring the PM to verify and correct what seemed to be the cause of a distorsion in communications among the stakeholders.

I’m leaving this post with a “dictum”: Data don’t say anything till you ask them the right question.

So, don’t try to find the right tool, but try to analyze the data instead.

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