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In doing so, we outline methodological challenges to studying Instagram, especially in comparison to Twitter.

Finally, we address critical questions around ethics and privacy for social media users and researchers alike, setting out key considerations for future social media research.

Research into social media has been carried out within and across numerous disciplines, further demonstrating the use of social media for multiple purposes and contexts (see, for instance, the perspectives represented in Weller, , 2014).

There has been a general trend, though, within Internet Studies and other, related fields, towards quantitative-driven, large-scale projects using automated processes to capture and analyse activity on social media platforms.

Using APIs provided by the platforms, publicly available data is collected and processed in large numbers, with rich datasets gathered.

Such projects provide the means for researchers to study extended online activity, uses of social media platforms and their evolution over time and across topics, and populations.

As boyd and Crawford (2012) note: “Too often, Big Data enables the practice of apophenia: seeing patterns where none actually exist, simply because enormous quantities of data can offer connections that radiate in all directions.” [1] Of course, big data is not synonymous with quantitative analysis (nor small data with qualitative), and there are important insights to be garnered from large-scale analysis and tracking; we advocate for mixed methods, combining quantitative and qualitative tools and insights, to take full advantage and explore more thoroughly the rich datasets collected from social media.

Spending time studying data through qualitative means is also critical to understanding how social media are used in non-standard ways, identifying practices that might easily be missed through automated analyses.

Social media research context Our exploration of Instagram occurs in the wider context of extended research into social media, from both qualitative and quantitative foundations.

These take into account a wide range of social media platforms, including apps as well as Web sites, and studying a wealth of practices and functions, concepts and affordances.

The prevalence of big data, aided by the availability of tools for capturing and processing large datasets, has been noted across disciplines, as have its limitations and pitfalls (see boyd and Crawford, 2012).

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