Content and Temporal Analysis of Communications to Predict Task Cohesion in Software Development Global Teams

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Virtual teams in industry are increasingly being used to develop software, create products, and accomplish tasks. However, analyzing those collaborations under same-time/different-place conditions is well-known to be difficult. In order to overcome some of these challenges, this research was concerned with the study of collaboration-based, content-based and temporal measures and their ability to predict cohesion within global software development projects. Messages were collected from three software development projects that involved students from two different countries. The similarities and quantities of these interactions were computed and analyzed at individual and group levels. Results of interaction-based metrics showed that the collaboration variables ... continued below

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Castro Hernandez, Alberto May 2017.

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  • Castro Hernandez, Alberto

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Description

Virtual teams in industry are increasingly being used to develop software, create products, and accomplish tasks. However, analyzing those collaborations under same-time/different-place conditions is well-known to be difficult. In order to overcome some of these challenges, this research was concerned with the study of collaboration-based, content-based and temporal measures and their ability to predict cohesion within global software development projects. Messages were collected from three software development projects that involved students from two different countries. The similarities and quantities of these interactions were computed and analyzed at individual and group levels. Results of interaction-based metrics showed that the collaboration variables most related to Task Cohesion were Linguistic Style Matching and Information Exchange. The study also found that Information Exchange rate and Reply rate have a significant and positive correlation to Task Cohesion, a factor used to describe participants' engagement in the global software development process. This relation was also found at the Group level. All these results suggest that metrics based on rate can be very useful for predicting cohesion in virtual groups. Similarly, content features based on communication categories were used to improve the identification of Task Cohesion levels. This model showed mixed results, since only Work similarity and Social rate were found to be correlated with Task Cohesion. This result can be explained by how a group's cohesiveness is often associated with fairness and trust, and that these two factors are often achieved by increased social and work communications. Also, at a group-level, all models were found correlated to Task Cohesion, specifically, Similarity+Rate, which suggests that models that include social and work communication categories are also good predictors of team cohesiveness. Finally, temporal interaction similarity measures were calculated to assess their prediction capabilities in a global setting. Results showed a significant negative correlation between the Pacing Rate and Task Cohesion, which suggests that frequent communications increases the cohesion between team members. The study also found a positive correlation between Coherence Similarity and Task Cohesion, which indicates the importance of establishing a rhythm within a team. In addition, the temporal models at individual and group-levels were found to be good predictors of Task Cohesion, which indicates the existence of a strong effect of frequent and rhythmic communications on cohesion related to the task. The contributions in this dissertation are three fold. 1) Novel use of Temporal measures to describe a team's rhythmic interactions, 2) Development of new, quantifiable factors for analyzing different characteristics of a team's communications, 3) Identification of interesting factors for predicting Task Cohesion levels among global teams.

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  • May 2017

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  • July 12, 2017, 3:17 a.m.

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Castro Hernandez, Alberto. Content and Temporal Analysis of Communications to Predict Task Cohesion in Software Development Global Teams, dissertation, May 2017; Denton, Texas. (digital.library.unt.edu/ark:/67531/metadc984118/: accessed November 17, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; .