Your SlideShare is downloading. ×
Analysing the practice of distributed software engineers: combining social network analysis and interaction analysis
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×

Saving this for later?

Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime - even offline.

Text the download link to your phone

Standard text messaging rates apply

Analysing the practice of distributed software engineers: combining social network analysis and interaction analysis

472
views

Published on

PhD Trial lecture delivered at University of Oslo, Faculty of Education 10.09-2010. …

PhD Trial lecture delivered at University of Oslo, Faculty of Education 10.09-2010.


0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
472
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
11
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Analysing the practice of distributed software engineers: combining social network analysis and interaction analysis
    Prøveforelesning/trial lecture 10.09-2010
  • 2. Lecture overview
  • 3. Software engineering
    Addresses all aspects of the software development process (Daintith & Wright, 2008).
    Increasingly a team-based activity (Elleithy, 2010).
    Technical aspects, but also a social process (Dittrich, Randall, & Singer, 2009).
    Requires co-ordination and communication.
  • 4. Time and place matrix adapted from Johansen (1988)
  • 5. Examples of geographically distributed software development projects
    Microsoft Windows operative system (Bird et al., 2009).
    Open source projects (seee.g. Lanzara, 2005).
  • 6. SocialNetwork Analysis (SNA)
    A theoretical perspective and research tools examining social structures.
    The study of social relations among a set of actors.
    The unit of analysis is an entity consisting of a collection of individuals and the linkages among them.
    Tabular form referred to as Adjacency matrix. Contain as many rows and columns as there are actors in the data set.
    (Wasserman & Faust, 1994)
  • 7. Basic network data (n=4)
    A1: Bill, A2: Steve, A3:Linus, A4: Edith
  • 8. Population boundaries
    Full network analysis
    Ego-centric network
  • 9. Network ties
    Defining what ties or relations to be measured.
    Online Interactions/communication patterns.
  • 10. A range of formal methods to represent social networks
    Mathematics and graphs.
    Computer assisted analysis.
    • i.e. a combination of Ucinet and NetDraw (www.Analytictech.com) .
    • 11. Recommended measures:
    • 12. Density
    • 13. Centrality
    • 14. Cliques
  • Density
    Density measures express the general level of cohesion in the social network (Scott, 2000).
    Defined by Garton, et al., (1999) as “the number of actually occurring relations or ties as the proportion of the number of theoretically possible relations of ties (p. 84).
  • 15. Degree centrality
    The number of other points that have a direct relation to that node. This is the sum of each row in the adjacency matrix representing the network(Freeman, 1979).
  • 16. Cliques and sub-groups
    A clique is a maximal complete sub-graph of three or more nodes (Wasserman & Faust, 1994).
    Sub-sets of actors who are more closely tied to each other (Hanneman, 2005).
  • 17. Example overlapping clique sets
  • 18. Example research study
    Communication networks in geographically distributed software development (Cataldo & Herbsleb, 2008).
    RQ1: Does a highly interconnected group of people take on a disproportionate share of overall communication?
  • 19. Communication patterns evolving over time
  • 20. Limitations of the study
    ”It is also worth pointing out that we did not have the opportunity to observe all communication, for example face-to face, telephone, and video conference.”
    (Cataldo & Herbsleb, 2008:587)
  • 21. Interaction analysis (IA)
    IA is an interdisciplinary method for empirical investigation of the interaction of human beings with each other and with objects of their environment. It investigates human activities, such as talk, nonverbal interaction, and the use of artefacts and technologies, identifying routine practices and problems and the resources for their solution.
    (Jordan and Henderson, 1995)
  • 22. Underlying assumptions
    Expert knowledge and practices are situated in the interactions between members of a particular community that are engaged with object and artefacts in their environment.
    Finds the empirical data in the details of social interactions extended in time and space.
  • 23. The use of video
    “Video technology has been vital in establishing Interaction Analysis” (Jordan & Henderson, 1995:1).
    Creates relatively permanent primary records.
    Group work analysis; Collaborative viewing of selected sequences of interaction.
    In-situ video recordings to reconstruct events.
  • 24. Framed by ethnographic fieldwork
    Video-based Interaction Analysis in conjunction with ethnographic fieldwork is quite common.
    “In the course of this ethnographic work, we attempt to identify interactional ‘hot spots’ -- sites of activity for which videotaping promises to be productive” (Jordan and Henderson, 1995:3).
  • 25. Distributed teams of software engineers
    Work environments spanning multiple physical locations.
  • 26. Observing distributed teams
    Capture interactions between team members, artifacts and objects at the different physical locations.
    Observing distributed team meetings such as video conferencing, screen logging and activity logs generated by CSCW-platform.
    Retrospective analysis; merging data from distributed sites in order to reconstruct complex interactions (Ruhleder, 2000).
  • 27. A combined approach?
    As analysts, to move from social interactions to their sum we need an instrument (Latour, 1996).
    Social network incorporated with video-based IA.
    Top down: Descriptive level, organize data to prepare for video-based IA. Providing an overview of the sum of interacting dyads in a communication network.
  • 28. Network framing
    • SNA as a framing for selecting ‘interactional hotspots’?
    • 29. Bottom up: account for distributed network relations when conducting micro analysis of social interaction.
  • Implications, pros and cons
    • The network stand leads us towards a relational perspective on social structure.
    • 30. Multisite video data. Micro level studies of moment-to-moment social interaction at the different physical sites.
    • 31. Combined in a retrospective analysis; sync or merge the activities across multiple locations.
    • 32. Complex, resource intensive design?
    • 33. May differ from the ”true” structure of the network (Wasserman & Faust, 1994).
  • References