C ODEBOOK ( SEE APPENDIX 11.3.2/11.3.3)

Page | 142 Questionnaire responses were coded by the researcher with the use of a codebook created for the study. Inspiration was taken from Neuendorf’s (2001) and

Krippendorff’s (2004) suggestions regarding the process of content analysis. The codebook was used in conjunction with the ‘Profile Content’ section of the

questionnaire, due to the openness for creativity and individuality under this section. Facebook provides users with certain ‘prompts’ to encourage disclosure within the individual’s profile. Answers to these prompts were analysed to explore differences in given disclosures. This part of the coding scheme was largely

inspired by Papacharissi’s (2006) pre-existing coding scheme for blog content analysis, which covers 3 aspects of content (Structure – e.g. extensiveness (word count); Design – e.g. vividness (presence of graphics), and interactivity (presence of invited feedback/ addressing the reader); and Content – e.g. formality of language and level of humour).

The user’s headline, current status, favourite quote and biography (referred to in the codebook as ‘Set of Prompts 1’) were coded in terms of total word count for each (as given by the Microsoft Word ‘Word Count’ feature). The status alone was also coded for grammatical convention. At the time of data collection Facebook status updates would start with the user’s name followed by their status presented as a sentence. As an observation it was noted that some users followed this

convention by writing in a somewhat third-person perspective (e.g. ‘NAME is

doing…’), whilst others ignored this grammatical format (e.g. ‘NAME Doing…’).

Statuses were coded 0 or 1 respectively. All “Favourite” prompts (i.e. Favourite Activities, Interests, Music, TV, Films and Books – referred to within the codebook as ‘Set of Prompts 2’) were coded in terms of number of distinct items within each prompt. This was thought to be a more adequate measure of the amount of

Page | 143 disclosures over total word count. For instance, users may still have a high word count even if disclosing just one favourite item, thus skewing results. To take this into account, prompts were also coded on their level of added description. Thus users who purely listed their favourite items (across all prompts) were coded ‘0’, whereas those who added any additional details or comments were coded ‘1’. For these prompts users were also coded on their level of specificity. Those who listed mainly specific items were coded ‘1’; whilst those who were more general, listing genres or generic descriptions were coded ‘0’. As an example, a user who had listed their favourite TV shows as “Eastenders, Family Guy and anything funny” would be coded 1 (as items are mainly specific), whilst a user writing “comedy and dramas” would be coded 0 as these are less specific.

Based on both prompt sets above, users were coded on several aspects of their disclosures across items with the categories ‘0’ (None) or ‘1’ (Present). Prompts were coded for the inclusion of ‘visual imagery’ (evidence of pictorial elements such as the inclusion of any images, emoticons or repetitive use of punctuation), ‘addressing the reader’ (evidence of feedback invitations, rhetorical questioning, or using the word “you” in reference to the person reading the content), ‘offensive language’ (any evidence of swearing or discussion of content which is overtly offensive), ‘self-deprecation’ (any evidence of overt false modesty, or negativity about self), ‘self-appreciation’ (any evidence of the user complimenting

themselves, even in a humorous fashion), and finally ‘humour’ (any evidence of overt humour, including popular acronyms LOL/LMAO and laughing emoticons). Many of these definitions were taken from Papacharissi (2006). Although the coding scheme may have benefited from a larger range of coding categories (for instance 0-5 varying in terms of frequency), it was felt that the subjective nature of

Page | 144 such items would be particularly difficult to code, and thus a dichotomous scheme would increase reliability of the coding process. Participants were also asked about the groups they had joined (with the inclusion of ‘pages’ due to the Facebook update). Whilst participants gave the total number of groups/pages joined, their supplied lists of such groups were coded under three distinctions, exploring the inclusion of offensive, random and serious groups. Offensive groups were defined as those containing offensive words in the title, or of an offensive context. Random groups were described as those that do not seem to have a point and do not tell you anything about the profiler’s likes or dislikes, such as “Join if your name begins

with…”. Serious groups were defined as those which support a particular cause, or

are concerned about a particular issue (e.g. charities/petitions). Again, codes were dichotomous using ‘0’ for None and ‘1’ for Present.

Finally, Haymes’ (1969, cited in Jourard, 1971) self-disclosure scoring manual, was also used to explore depth of self-disclosure. Haymes provides an in-depth scoring procedure to recognise any occurrences of emotions, self-awareness, needs or dreams which would signify a deeper level of disclosure. The scale has been adopted by several researchers to explore offline disclosure in interaction (Jourard, 1971). Although the scoring manual suggests that each of these occurrences should be coded on a scale of 0-2, a simplistic categorisation of 0-1 was used due to the subjective nature of the coding and the amount of text being coded. The manual provides examples for each occurrence. For instance, the expression of emotions can be seen within overt sentences of one stating how they feel (e.g. “it drives me crazy…”). The expression of needs is assessed by the

presence of any demands (e.g. “all I want is…”). Self-awareness includes an overt discussion of one’s capabilities and boundaries (e.g. “it’s really bad for me when

Page | 145 I…”). The expression of dreams is characterised by disclosures of ambitions (e.g. “I dream of the day when…”) (Haymes, 1969). The inclusion of any of these items led to a coding of 1 being given to signify a deeper level of disclosure.

The items explored were thought to add a level of added depth to the profile analysis beyond previous research, as well as holding relevance to the findings of the previous chapter.