Adding and finding meaning in case-by-case network graphs of interviews

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Information about Adding and finding meaning in case-by-case network graphs of interviews

Published on February 16, 2014

Author: FrankvanderMost1



This is a presentation that I gave at the e-Humanities Group on 31 October 2013 in Amsterdam.

For the ACUMEN project, I collected career data from and conducted interviews with about 40 university-based researchers and 10 deans, department heads and human resources managers. Career data typically comes in the form of CVs, which are suitable for storing and coding in relational databases. Doing interviews results in notes, transcriptions and coding added to the transcriptions. This is usually done with coding software such as NVIVO, Atlas or TAMSAnalyzer. Database software does not produce network graphs. Coding software is good at producing network graphs, but bad at dealing with relational data. The problem then is how to combine the two. For the ACUMEN project, I explored a few possibilities. I will present one of these and evaluate its use as a tool for exploration and analysis.

Adding and finding meaning in case-by-case network-graphs of interviews Frank van der Most ! e-Humanities group and DANS ! New Trends in e-Humanities, 31 October 2013 1

What does it mean? !2

A practical research problem ✦ ± 50 interviews •Fairly structured •transcribed and coded ✦ Interested in a sub-set (27), on a sub-topic, viz. informal evaluations ✦ How to get an overview? ✦ Okay, let’s try visualizing instead of reading !3

The raw material ✦ Interviewee info: date of birth, date of PhD, CV-events ✦ 3 Most important developments + 3 most influential evaluations •Event code + Event-code group •Info about event: period, country, affiliation summary ✦ Coded interview transcriptions •Importance •Micro-stories !4

Tuesday, 13:47 6 Interviewees Importance

Tuesday 14:40 10 Interviewees Importance Micro-stories

Tuesday 14:40

Tuesday 16:33 20 Interviewees Importance

Tuesday 16:33

Does a table work better? Importance count importance>long_term_stability 8 importance>family 6 importance>doing_research 6 importance>academia_or_not_question 5 importance>enjoying_one_s_work 5 importance>having_the_necessary_skills_or_qualifications 4 importance>mobility 4 importance>personal_achievement 4 importance>societal_impact 4 importance>academic_standing 4 importance>contacts_or_network 3 Yes for quantitative overview, still no for qualitative

Wednesday, 16:19

Thursday, 11:45

Thursday, 16:30

Thursday, 16:30

Thursday, 16:30

Thursday, 16:30

Thursday, 16:30

Thursday, 16:30

Saturday, 11:53

Sunday, 19:23

Monday, 20:10

Recap, what can we see and what it means Tim e/ sp ac e it y ar co n ne cti o E nt ve ns cror mi ce o r tan o ities Imp ilar sim t or y s il sim pe -ty

Dominant shape

What we can not see (but may read) ✦ Time dimension ✦ interviewee info and ✦ Geography ✦ Relations between ‘importance’ and ‘microstories’ !41

Relations between ‘importance’ and ‘micro-stories

Thank you for your attention io t s e u Q ? s n Com m en t s ? !44

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