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Analysis of Qualitative Data: Using Automated Semantic Analysis to Understand Networks of Concepts

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Collaborative Research Design

Abstract

Qualitative research of business relationships and networks is of limited value if the analysis does not address the rich interdependencies of the processes and mechanisms involved and does not feature clear and credible methods of analysis. The purpose of this chapter is to consider approaches to analysis that provide opportunities for demonstrable, credible analysis of the qualitative nuances of business systems. The particular focus is on the use of computer-aided methods, including the Leximancer lexicographic analysis software, that, combined with more traditional methods, provide reliable and meaningful analysis of large quantities of textual information, including interview transcripts and secondary data. These processes and the findings that they can produce are demonstrated using a wide range of the authors’ own research.

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Acknowledgements

We would like to thank our co-researchers, Tamsin Angus-Leppan, Sue Benn, Christine Burton, Kerry Daniels, Sara Denize, Winie Evers, Sana Marron, Chris Medlin, Andrew Smith and Ian Wilkinson for the work done with us on the projects presented in our examples. A special acknowledgement goes to the developer of Leximancer, Andrew Smith, for his amazing vision in developing Leximancer and tremendous help over an extended period of research.

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Correspondence to Kristin B. Munksgaard .

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Appendix

Appendix

Ranked concept lists for five research phases of Advertising Project (presented in Evers et al. 2017).

Phase, interview 1

Phase 2, workshop 1

Phase 3, interview 2

Phase 4, workshop 2

Phase 5, workshop 3

Name-like

Count

Rel. (%)

Name-like

Count

Rel. (%)

Name-like

Count (%)

Rel. (%)

Name-like

Count

Name-like

Count

Rel. (%)

Marianne(firm Owner)

141

74

Marianne(firm Owner)

66

90

Marianne(firm Owner)

130

100

Marianne(firm Owner)

27

Marianne (firm owner)

102

100

Kalb (firm Name)

141

74

Kalb (firm Name)

52

71

Kalb (firm Name)

110

85

Kalb (firm Name)

26

Kalb (firm Name)

85

83

      

Kirsten (firm Employee)

28

22

  

Kirsten (firm Employee)

23

23

Word-Like

Count

Rel.

Word-Like

Count

Rel.

Word-Like

Count

Rel.

Word-Like

Count

Word-Like

Count

Rel.

kunder (customers)

191

100

kunde (customer)

73

100

kunder (customers)

117

90

opgave (task)

70

mĂĄde (the way)

94

92

opgave (task)

130

68

vores (our)

48

66

se (see)

106

82

kunde (customer)

63

opgave (task)

90

88

forhold (relation)

100

52

opgave (task)

47

64

forhold (relation)

103

79

forhold (relation)

61

kunde (customer)

84

82

tid (time)

89

47

sammen (together)

46

63

sammen (together)

84

65

tillid (trust)

43

forhold (relation)

81

79

virksomhed (company)

85

45

virksomhed (company)

42

58

store (large)

74

57

sammen (together)

42

sammen (togeteher)

54

53

vores (our)

75

39

tid (time)

38

52

arbejde (work)

61

47

netvaerk (network)

40

huske (remember)

52

51

se(see)

75

39

forhold (relation)

37

51

virksomhed (company)

53

41

hjertet (the heart)

39

giver (gives)

39

38

sammen (together)

68

36

finde (find)

31

42

vigtigt (important)

47

36

store (large)

38

se (see)

36

35

store (large)

58

30

se(see)

31

42

finde (find)

43

33

vej (pathway)

37

finde (find)

35

34

arbejde (work)

49

26

arbejde (work)

29

40

vores (our)

43

33

partnere (partners)

35

tid (time)

33

32

del (share)

44

23

relation (relation)

27

37

opgaver (task)

42

32

arm (arm)

32

rigtige (right)

29

28

indtryk (impression)

43

23

handler (act, trades)

27

37

 bruge (use)

 41

 32

spaendende (exciting)

26

vigtige (important)

27

26

fald (decrease)

42

22

udfordringer (challenges)

 24

 33

tid (time)

41

32

se (see)

24

meaning (opinion, meaning)

25

25

virksomheden (the firm)

41

21

store (large)

23

32

giver (gives)

37

28

giver (gives)

22

tiltælde (coincidence)

25

25

forskellige (different)

41

21

for (before)

21

29

prøve (try)

34

26

arbejde (work)

22

samarbejdspartnere (parteners)

24

24

prove (try)

41

21

lose (solve)

20

27

maerke (sense)

34

26

rigtige (proper)

21

del (share)

24

24

finde (find)

37

19

giver (gives)

20

27

del (share)

33

25

bedre (better)

19

sker (happen)

24

24

vaerdi (value)

35

18

hjaelpe (support)

19

26

mulighed (opportunity)

32

25

finde (find)

17

bedre (better)

24

24

nye (new)

33

17

behov (needs)

19

26

konkret (concrete)

32

25

tid (time)

17

hjertet (the heat)

23

23

pr (pr)

32

17

medier (media)

19

26

netvaerk (network)

32

25

penge (money)

17

vej (pathway)

22

22

tilbage (back)

30

16

penge (money)

18

25

samarbejdspartnere (partners)

27

21

prøve (try)

15

før (before)

22

22

kommunikation (communication)

29

15

muligheder (opportunities)

15

21

medier (media)

25

19

  

samarbejde (collabration)

22

22

lille (small)

26

14

        

tilbage (back)

22

22

           

større (larger)

21

21

           

prøve (try)

19

19

           

bruge (use)

19

19

           

forskellige (different)

19

19

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Young, L., Munksgaard, K.B. (2018). Analysis of Qualitative Data: Using Automated Semantic Analysis to Understand Networks of Concepts. In: Freytag, P., Young, L. (eds) Collaborative Research Design. Springer, Singapore. https://doi.org/10.1007/978-981-10-5008-4_11

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