Big Data in Communication Research: A contextual turn? – An IAMCR pre-conference

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Update: This was initially planned as a hybrid pre-conference. On 16 May Xi’an Jiaotong-Liverpool University (XJTLU) in Suzhou, host of the pre-conference, announced that due to a recent outbreak of COVID 19 in the city the conference will be online only. The detailed pre-conference programme is available here

Date and time

Friday 8 July 2022: | 09:00 – 18:00 (Beijing time) ; 01h00 – 10h00 (UTC)|

Description

Recent advances in communication studies have seen much greater attention paid to the development, appropriation, and reflection on computational methods for analyzing large and heterogeneous data. Despite its considerable contributions, big data analytics has been criticized for the lack of contextual consideration for a long time. In other words, scholarships with computational methods may suffer from the pitfall of not unpacking, recognizing, and theorizing the richness of associated contextual elements in (big) data. This preconference aims to address such issues by advancing a context-aware approach in computational methods and by articulating an interrogation of contextual elements in using computational methods. A context-aware approach in computational methods is particularly valuable to IAMCR as a worldwide professional organization in the field of media and communication research, as this approach recognizes a reality where people communicate in diverse ways against different contexts.

To acknowledge and explicate such context-bound ways plays a crucial role to explain variation in communication practices and networks, and to appreciate the plurality of communicative phenomena across the globe.

We thereby invite original and rigorous contributions and reflections based on big data and contextual analysis. We hope to engage with opportunities and challenges of advancing context-aware approaches in computational methods. The submissions can be theoretical or based on empirical studies, but would also include innovative suggestions to overcome research challenges like the lack of contextual consideration.

Location

An online Zoom conference.

Participation and registration

Participation at the event is free of charge, but registration is compulsory. Please use the following link to register by 1 July 2022. 

https://liverpool-ac-uk.zoom.us/j/2304061092?pwd=OGlzby9DU3FiaHQ5bjhUdTdZT2RYQT09

Meeting ID:230 406 1092
Code:iamcr2022#

Keynotes and programme

Keynote Speech 1: Friday, 8 July 2022  09:15 – 10:15 (Beijing time)| 01h15 - 02h15 (UTC) 

Computational communication research: Challenges and opportunities
Cuihua (Cindy) Shen, University of California, Davis, USA; Chair, Computational Methods Division, the International Communication Association (ICA).

Keynote Speech 2: Friday, 8 July 2022 16:50 – 17:50 (Beijing time) | 08h50 - 09h50 (UTC)

The Power of Babel: How the neglect of linguistic and cultural diversity undermines the advance of computational communication science
Christian Baden, Hebrew University of Jerusalem, Israel.

The detailed programme is available here.

For inquiries, please email:  iamcr.compmeth@gmail.com

Language

English will be the event's working language.

Convenors and organisers

  • Jun Liu, the Center for Tracking and Society and Department of Communication, University of Copenhagen, Denmark. 
  • Xianwen Kuang, Department of Media and Communication, Xi'an Jiaotong-Liverpool University, China. IAMCR Beijing 2022 Local Organizing Committee Member and IAMCR member. 
  • Simon Schweighofer, Department of Media & Communication, Xi'an Jiaotong-Liverpool University, China.

In collaboration with Cuihua (Cindy) Shen, Department of Communication, University of California, Davis, & Chair, Computational Methods Division, the International Communication Association. 

With the support of the Computational Methods Division of the International Communication Association and the Independent Research Fund Denmark Sapere Aude Research Leaders Project (1055-00011B).

Contact email

iamcr.compmeth@gmail.com