On content analysis of images of mass protests: a case of data triangulation

Abstract

The article discusses the methodological issues related to the content analysis of visual records of mass protests. Two categories of visual records are differentiated and compared: media coverage (documentary photography) and images from private collections (street photography). A sample of 382 images taken of the December 24, 2011 demonstration in Moscow, Russia is used for the purposes of the content analysis. The outcomes are compared with results of a survey administered among the protesters (N =791). It is argued that street photography produces a more valid visual account of the protest. The content analysis of visual records can complement the other methods for studying mass protests (survey research, qualitative in-depth interviews, participant observation, and network analysis of the social networking sites), particularly if no other data is available.

Curbing protest through elite co-optation? Regional protest mobilization by the Russian systemic opposition during the ‘for fair elections’ protests 2011–2012

“…. However, if such powersharing reduces contention, this effect would still prove the taming influence of democratic institutions (parties and parliaments) on opposition actors in electoral authoritarian settings.9 For a positive assessment of the use of visual materials in protest research seeOleinik (2015).…”

Image Clustering: An Unsupervised Approach to Categorize Visual Data in Social Science Research

“…This article contributes to the burgeoning study of "image as data" by synthesizing practical steps and methods of unsupervised image clustering for social scientists. Image data are abundant in the current social media age, but so far, the analysis of image data in sociology still heavily relies on researchers looking at images and summarizing common themes through traditional content analysis techniques (Krippendorff, 2004;Corrigall-Brown and Wilkes, 2012;Rohlinger and Klein, 2012;Oleinik, 2015). Human reading of images is subject to reproducibility issues even for small datasets, and to scalability concerns for larger image datasets.…”

“…Image data have been frequently used by sociologists to explore meanings, such as inferring protesters' emotions during protests (Corrigall-Brown and Wilkes, 2012;Oleinik, 2015), understanding how media frame abortion issues (Rohlinger and Klein, 2012), or studying terrorists' visual propaganda strategies (Baele et al, 2020). In these studies, researchers rely on content analysis techniques by looking at images piece by piece and summarizing common themes by hand.…”

Evaluación diagnóstica de necesidades en un equipamiento de educación ambiental mediante la triangulación múltiple de datos

“…As a contrast technique, it reveals the contradiction, inconsistency or convergence between data obtained by different sources, as proven by, among others, the works of Bjurulf et al (2013), Brown et al (2015), Flick (2005), López et al (2013), Teixeira et al (2012), Van Drie and Dekker (2013). In addition, with Barusch et al (2011), Bekhet and Zauszniewski (2012), Beattie et al (2005), Hind (2017), Newman et al (2013), Oelinik (2015), Okoe and Boateng (2016), Schraeli et al (2017), Stutz (2016) and Torrance (2012), we can affirm that triangulation strategies allow the exercise of quality control over qualitative research processes, offering confidence tests and guarantees that the results and findings proposed there meet minimum requirements of credibility, rigor, veracity and robustness.…”