H.U.M.A.N. Data Session Report

By Betül Çimenli, PhD candidate at Middle East Technical University (METU), Research Assistant at Bartın University

Merve Bozbıyık, Research Assistant at Middle East Technical University (METU), PhD Candidate at Hacettepe University

What is HUMAN?

Hacettepe University Micro Analysis Network (HUMAN) – based in Hacettepe University, Turkey – was founded by Dr. Olcay Sert, Dr. Ufuk Balaman (current director), Dr. Nilüfer Can-Daşkın (current vice director), and Dr. Safinaz Büyükgüzel in 2015. Being the first conversation analytic community in Turkey, The HUMAN Research Centre aims to explore social interactions in various ordinary and institutional settings by (mainly) using conversation analytical framework. In addition to regular events such as the Reading Group and HUMANtalks, HUMAN members also hold weekly CA data sessions (in English or Turkish) every Wednesday at 3:00 p.m. for six years.

HUMAN has organized over 130 data sessions until now, holding them online via Zoom since the beginning of the pandemic. During the data sessions, researchers can share their conversation analytic findings to get feedback regarding their transcriptions and analyses. Participants utilize both English and Turkish CA terminology based on the language of the data. In addition, HUMAN researchers make publications and presentations in a collaborative way and design and participate in (inter)national projects. Thus, these events contribute to expanding CA research knowledge in different languages (Turkish, English, German) to other places and academics through various HUMAN events at local and global contexts.

What happens before the sessions?

The group’s directory calls for data sessions before academic terms start (Fall and Spring) in Turkey. Anyone who learns about this call may choose a number of appropriate slots for his/her possible data session. When the directory finalizes the sessions for a term, they announce them via a flyer. Before each session, a reannouncement for that particular week is posted on social media and the meeting details are shared through email (to only subscribed members).

How does a session unfold?

Each session starts with a brief overview of what we do in a regular CA data session in HUMAN since we might have a couple of newcomers who might not be familiar with the conversation analytic framework or have not attended any data sessions before. Through this, new participants have a chance to better observe how we analyse data and even contribute to the ongoing discussion if they feel like doing so. We hope that having participants with varying levels of proficiency in terms of CA knowledge and practice will be a learning opportunity for every one of us, especially the ones new to the field. 

Following the brief introduction (also see Hutchby & Wooffitt, 2008 for the analysis procedure), the participant(s) who brings one or two extracts from a larger dataset introduce their data by giving only relevant and vital information about the context (e.g., where the interaction was recorded) and participants (e.g., who are in the recording), the placement of the extracts in the larger dataset (e.g., at which hour, from which week) etc. Extracts totally should last for around one minute while the size of the dataset is not an issue here. That is, data may come from a larger project including hours of recordings or an emergent collection including only a couple of hours. A crucial point here is that the researchers who bring the data do not reveal their phenomenon or potential research foci based on that piece of data. Instead, they wait until other researchers are done with their analyses and discussions on the whole extract to reveal their own focus. We emphasize this ‘secrecy’ to ensure an authentic ‘unmotivated look’ (Sacks, 1984; ten Have, 2007) into data. Furthermore, the researchers who bring the data have the chance (i) to observe how others approach their data, (ii) to broaden their perspectives towards their own data through different analyses focusing on different parts or aspects of the data, (iii) to receive instant feedback on their transcription and analysis and thus ensure the reliability of their analysis. 

Following this, they share their password-protected transcripts and recordings stored in the cloud of HUMAN, with the participants of the online meeting. Participants are always reminded not to store or share the recordings or transcriptions of the extracts. This is preferred to protect the privacy of participants and data. The transcripts mostly follow Mondada (2019) or Jeffersonian (2004) conventions. When we have transcriptions in languages other than English, the participants who share their data with HUMAN researchers mostly choose to prepare two-line or sometimes three-line transcripts (original talk, word-by-word gloss, idiomatic translation) depending on their research purposes. They do not generally prefer a three-line transcription, though, as it gets harder to follow it and our main aim is to analyse the data, not to present it in a perfect way as in a manuscript. 

The actual data analysis phase starts here with transcript sharing. We have 10 minutes to examine the transcripts by watching/listening the recordings simultaneously on our devices. Before COVID-19 pandemic, the video/audio recording was played ten times at most, and then each participant took the floor to share their comments after working on the focal extract individually. Then volunteers share their ideas on any part of the transcript that needs revision, editing, re-examination, addition, or omission in terms of any segmental and suprasegmental features. Following this, we spare 15 to 20 minutes for ‘analysis time’ at most, during which we mute ourselves and turn-off our cameras to individually play the video as many times as we want and do our own analysis.

After this allocated time is over, all the participants come back to the meeting and use the ‘raise hand’ button to share their analyses and insights based on the data. That is, on a first come first served basis, starting from the one who raised her/his hand first, we share our minute-by-minute and sequential CA analysis. However, if one has something to contribute to the ongoing analysis, s/he can just take the turn after the current speaker. And, if one has nothing to add to the analysis or discussion, s/he may just stay silent throughout the session. So, if one does not raise his/her hand to take the floor, s/he can only listen to the discussion without feeling any pressure to contribute to the discussion. When all the volunteer participants have shared their insights, the researcher(s) who brought the data take the floor to share what the focus (phenomenon) is in the focal extract, ponder on how they are similar to or different from current discussions in the session by also making connections with the larger set of their data. Finally, we have a general discussion on what we have found in the extracts and how many different phenomena might come out of this, which are worthy of further investigation. 

Wanna be involved?

The group is open for any (inter)national participants as 99% of the sessions are held in English. You can click on https://microanalysisnetwork.com/ to get more information about the HUMAN Research Centre, and follow our Twitter account (https://twitter.com/Micro_Analysis_).

You can also send an email to microanalysisnetwork@googlegroups.com to be included in the mailing list to receive weekly emails regarding the data sessions and other events that HUMAN Research Centre organizes. 

Addendum

Recently, a non-EMCA researcher, who has never contributed to HUMAN, has been appointed as the new director and the HUMAN team has been taken outside the organizational body of the Research Centre. As the HUMAN team, we were left without HUMAN and now temporarily use Micro Analysis Network as the name of the group and are looking for a new name and new ways to contribute to building the future of EMCA research in Turkey.

References

Hutchby, I., & Wooffitt, R. (2008). Conversation analysis. Cambridge: Polity.

Jefferson, G. (2004). Glossary of transcript symbols with an Introduction. In G. H. Lerner (Ed.) Conversation analysis: Studies from the first generation (pp. 13-23). Philadelphia: John Benjamins.

Mondada, L. (2019). Conventions for transcribing multimodality. Lorenza Mondada. https://www.lorenzamondada.net/multimodal-transcription

Sacks, H (1984). Notes on methodology. In J, Atkinson, & J. Heritage(Eds.) Structures of Social Action.  Cambridge: Cambridge University Press, pp. 21–27.

ten Have, P. (2007). Doing conversation analysis. London: Sage.

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