Social Media: Uses and Challenges in Litigation

Social media has become an integral part of everyday life. It has changed the way people interact, communicate, and consume information. Its widespread use provides unprecedented insights into consumer motivations, experiences, perceptions, and reactions. These insights can serve as an important source of evidence in litigation. This article identifies how social media data may be used across different types of litigation and addresses some practical challenges. 

What is Social Media Data?

Social media is the modern version of word of mouth. It is a collection of online platforms and technologies where individuals can share information, divulge opinions, and form social connections. Popular social media platforms include Facebook, Instagram, LinkedIn, Reddit, X (formerly Twitter), and YouTube. Consumer messages and reviews can also be found on e-commerce platforms and other websites. Social media data has important characteristics that make it a potentially valuable source of evidence in litigation.

Social media is continuous

Social media encourages consumers to stay active. This can produce highly descriptive and high frequency data sets that can lay the foundation for rich inquiries into consumer perceptions and behaviours. In addition, data collected over time can assist with causal inference studies that aim to infer the reasons for consumers’ purchasing decisions. 

Social media provides a window into consumer behaviour

Consumer comments can shed light on how marketing messages are perceived, which product or service features are considered important, and why consumers may have made purchasing decisions.

Social media is often reactive

Relative to surveys, online consumer reflections can capture perceptions at, or close to, the time of a relevant event. 

Functions of Social Media Data in Litigation

Social media data can be applied across a range of litigation matters. Social media data can be used to gather evidence of wrongdoing, authenticate data sources, uncover relationships between individuals and entities, provide temporal insights, reveal drivers of economic value, and address causal inference questions. 

Functions of Social Media Data

Evidence

Social media data can serve as a direct source of evidence of wrongdoing or false claims. For example, in fraud matters, social media data may indicate the time, location, and activity of an individual. In a personal injury matter, an image or video footage may expose the Plaintiff’s physical condition or abilities at a specific time. In intellectual property matters, social media may help identify unauthorised use, demonstrate whether consumers are confused by similarities between trademarks, or whether a trademark has acquired distinctiveness. In governance cases, social media data may be used to investigate claims of discrimination or misconduct. Social media posts by companies may also be subject to disclosure claims.

Authenticate

Social media data can validate information obtained from traditional sources of evidence. For example, in fraud matters, social media data can corroborate evidence of theft. Photographs showing purchases of luxury cars may indicate that an individual was living beyond their financial means. Social media data can also be used to complement information collected through consumer surveys. Surveys and social media data address similar issues of consumer behaviour but do so using different analytical approaches and at different points in time relative to the event.

Network

Social media data can help establish relationships between individuals and entities. This creates a more complete profile of key individuals in a case. Artificial Intelligence (AI) can identify networks of individuals who are connected on online platforms. AI can also infer the strength of relationships based on the frequency, timing, and topics of conversations between individuals. Potential applications include fraud and bribery cases where understanding relationships may generate hypotheses about possible financial flows.

Time

Social media data can provide important temporal context. For example, understanding when certain information was exchanged or where that individual was located at a certain time may be useful when assessing an individual’s conduct. Temporal information may also be useful in relating two different sources of information to help with tracing. For example, in a fraud matter, dates on photographs posted on social media can be compared to dates of large withdrawals from bank accounts.

Value

Social media data can reveal shifts in attitudes before and after an allegedly defamatory or misleading statement. In intellectual property matters, social media data can help infer the relative importance of product characteristics or attributes. For matters concerning the quality or defectiveness of specific product features, social media data can be used to assess the average consumer’s perception of the quality of those features.

Causal Inference

Social media data can help infer the causes of economic phenomenon. For example, in a business interruption matter, social media data may reveal why customers cancelled their membership or returned their products. Similarly, in a securities matter, social media data may contribute to an understanding of why stock prices changed at a certain time.

Challenges to Social Media Data in Litigation

The application of social media data to litigation contexts faces three main challenges. First, there is the question of reliability. Anonymised posts, paid influencers, and bot reviewers can undermine the confidence of social media data. Second, preservation and access to data may be limited, especially as companies respond to privacy concerns by restricting third party data access. Third, from a practical perspective, social media data is unstructured in the sense that it can be disorganised and inconsistently presented. However, the emergence of Natural Language Processing (NLP), a sub-field of AI, in recent years has dramatically improved the efficiency of working with textual data.

Reliability and data access issues are neither unique nor insurmountable. Surveys have long been subject to a host of non-sampling errors, including respondents who misrepresent themselves. Social media data sets can be scrutinised, including through the use of frameworks and tools to identify inauthentic content. Further, restrictions on third party access can be overcome through discovery requests and/or by using alternative social media platforms.

Conclusion

Social media data provides an unprecedented tool for understanding consumer perceptions and actions. As such, it represents a potential source of valuable evidence for addressing liability and materiality issues across a diverse range of litigation contexts. While the use of social media data faces challenges, these can be overcome by applying scrutiny to the data sources and by anticipating access issues early in a case.

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