Mood-Based Micro-Blogging in Distributed Software Engineering

Talk presented at MSR 2013, the 10th Working Conference on Mining Software Repositories.

Paper: http://aspic.nl/publications/DullemondGamerenStoreyDeursenMSR2013.pdf

Transcript

1. Mood-­‐Based  Micro-­‐Blogging  
   Kevin  Dullemond,    Ben  van  Gameren,    
   Margaret-­‐Anne  Storey,  Arie  van  Deursen  
   Mining  So;ware  Repositories  (MSR),  San  Francisco,  May  2013   1  
   

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2. Micro-­‐Blogs  
   •  “Short  messages  people  use  to  provide  updates  
   on  their  ac5vi5es,  observa5ons  and  interes5ng  
   content,  directly  or  indirectly  to  others”  
   •  Use  in  so;ware  engineering:  
   – Support  awareness?  
   – Support  distributed  working?  
   Ehrlich  et  al:  
   “Microblogging  inside  
   and  outside  the  
   workplace”,  ICWSM,  2010  
   2  
   

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3. IHomer  Creates  WeHomer  
   WeHomer  @  iHomer:  
   Miro-­‐Blogging  with  Moods  
    
   >L      L      K      J      >J  
   3  
   

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4. Today’s  MSR  keynote  
   4  
   

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5. 5  
   I’m  going  to  be  a  daddy!    :-­‐D  
   Will  be  partly  available  today;  Son  is  sick  at  home  >L  
   Working  on  our  Linux  servers  today  –    
   some  services  may  experience  outages  J  
   On  my  way  to  customer  X  for  first  live  test  :-­‐D  
   

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6. 1  year  usage  data;  
   2500  messages  
   Mood  is  actually  
   indicated  
   6  
   

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7. Approach  
   •  Try  to  understand:  
   – Role  of  micro-­‐blogging  in  
   distributed  work  @  home  
   – Role  of  “mood”  
   •  Qualitadve  analysis  
   – Coding  2500  posts    
   from  20  users  
   – Interviews  with  5  users  
   Content
   Information about
   a person
   Health
   Sentiment
   Personal
   Experience
   Information about
   technology
   Technical
   Knowledge
   Information about
   task articulation
   work
   Work Planning
   Work Assignment
   Supplies
   Non-Technical
   Infrastructure
   Technical
   Infrastructure
   Intern
   Technical
   Infrastructure
   Extern
   Information about
   customer
   relations
   Relation
   Project
   Commissioning
   Information about
   entrepreneurial
   tasks
   Prospects
   Company
   Meeting
   Applicant
   Invoicing
   7  
   

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8. “Nature”:    
   Most  Posts  Are  Posidve  
   8  
   Manual  sendment  analysis.  
   Largely  in  line  with  indicated  “happiness”  
   

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9. “Form”:    
   9%  of  Posts  is  a  Quesdon  
   9  
   Ehrlich  et  al  BlueTwit  analysis:  13%  quesdons    
   

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10. “Intendon”:    
    Personal,  Work,  Coordinadon  
    10  
    “Task  ardculadon”  work  
    Home  /  work  balance  
    

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11. “Content”:    
    Intra-­‐  And  Inter-­‐Team  Topics  
    •  Intra-­‐team  (4  teams,  2-­‐7  members)  
    – Directed  messages:  more  within  team  
    – Planning  and  coordinadon  
    •  Full  organizadon  (20  people):  
    – New  employees,    new  prospects,  new  business  
    direcdons,  social  events  
    – Planning  and  coordinadon  
    •  “Glue”  between  people  working  at  home.  
    11  
    

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12. The  Tuesday  Effect  
    12  
    “There  is  no  halfsies  in  a  distributed  team  …  
    If  even  one  person  of  the  team  is  remote,  very  single  person  has  to  
    start  communica5ng  on  line.”  –  Fullerton  /  StackExchange  
    

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13. Discussion  
    •  Social  interacdons  affect  so;w.  development  
    – Mining  research  must  be  aware  of  them!  
    – To  what  extent  should  we  mine  them?  
    •  Mood  indicators?  
    – Issues,  feature  requests,  commits,  pull  requests?  
    •  Sendment  analysis?  –  Anger  versus  Joy  
    13  
    

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14. Conclusions  
    •  Micro-­‐blogging  with  mood  indicators:  
    – Share  knowledge  and  emo5ons  like    
    you  are  co-­‐located  
    – Create  and  sustain  a  feeling  of  connectedness  
    (conform  Zhao  et  al,  ICWSM  2009)  
    – Beyond  individual  projects  
    •  All  or  nothing  proposidon  (Tuesday  effect)  
    14  
    

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