In this work of Master thesis, we target three platforms related to software development (StackOverflow, GitHub, and Twitter). One of the first contributions is the design and building of a database on these three platforms, as a result of a complex phase of crawling, extraction and matching of 58K user profiles and their respective
interaction networks. By capitalising on this dataset, we characterise different types of user expertise within and across professional-oriented online platforms, and operationalise the notions of ubiquitous and specialist expertise. We investigate how personal and relational triggering stimuli impact on the within- and across-network
expert activities; how the users’ reputation vary across networks; and how they tend to form communities in different networks. Results show the importance of identifying and analysing different types of expertise traits across social platforms, as a mean to better characterise expertise and its online manifestation.
Devo inserire l’immagine sulla domanda, e descrivere qualche tratto che la caratterizza? (es. tag, code snippets, etc.)
Devo inserire un caption sotto l’immagine (es. «Esempio di domanda su StackOverflow»)
Devo inserire l’immagine sulla domanda, e descrivere qualche tratto che la caratterizza? (es. tag, code snippets, etc.)
Devo inserire un caption sotto l’immagine (es. «Esempio di domanda su StackOverflow»)
Devo inserire l’immagine sulla domanda, e descrivere qualche tratto che la caratterizza? (es. tag, code snippets, etc.)
Devo inserire un caption sotto l’immagine (es. «Esempio di domanda su StackOverflow»)
Inserire una voce per «Azioni individuali» e «Azioni relazionali»? (al posto di domande SO, da inserire solo nel discorso)
Starting from a set of cross-matched users between StackOverflow and GitHub, we decided to develop a software module capableto match users with Twitter profiles
Twitter platform provides two ways to search for user profiles: Lookup and Search. Because of a computational gap betweenthe techniques, we decided to make some studies about when to perform User Search instead of User Lookup.
We also performed a Precision study about how to match user profiles: we chose website, profile pictureand name as fields to be analyzed for matching purpose
We have 707k profiles searched on Twitter,despite of 604k distinct StackOverflow{Github matches, because we decided to useall useful data provided by each user The overall result counts 64.353 matches byadding Lookup and Search matches. Otherwise, we have a final number of 58.710unique Twitter matched profiles.
Inserire i dettagli sui test Spearman’s Rho
Inserire i dettagli sui test Spearman’s Rho
Inserire i dettagli sui test Spearman’s Rho
Inserire i dettagli sui test Spearman’s Rho
Inserire i dettagli sui test Spearman’s Rho
Inserire i dettagli sui test Spearman’s Rho
we first categorized the Github login names into the following classes: 1) the login containsonly lower-case characters, 2) it contains at least one upper-case character, 3) itcontains numbers, and 4) it contains special characters.
we first categorized the Github login names into the following classes: 1) the login containsonly lower-case characters, 2) it contains at least one upper-case character, 3) itcontains numbers, and 4) it contains special characters.