Online discussions that gather momentum on social media play a crucial role in shaping our world. They influence everything from voting decisions, to the information we consume, to our response to global crises like pandemics. However, we need to pay attention because these conversations often do not have an organic origin; they can be orchestrated by influence campaigns that aim to spread misinformation and thus contribute to dividing society. In this context, social media trends shape public opinion, rather than public opinion dictating trends.
In 2020, Mozilla Firefox announced the Social Media Analysis Toolkit (SMAT) to address the challenges of manipulated online discussions. Mozilla Fellow Emmi Bevensee was a co-developer, and it is a free, easy-to-use and open-source tool designed to screen digital conversations.
Governments around the world showed their technological strength during Covid-19 by installing mechanisms to monitor people and business behavior, often using apps like SMAT.
This app, positioned as a resource for activists, journalists, researchers and social organizations, plays a crucial role in understanding digital discussions and social dynamics.
For example, SMAT conspicuously provides specific tools for monitoring US elections. These tools include interactive network graphs that map the spheres of influence and partisanship of politicians. Researchers, journalists, and activists can leverage SMAT to explore a spectrum of information, from trending topics during specific timeframes to identifying key influencers driving conversations, as well as analyzing the most shared links.
Functions and possibilities:
SMAT offers a range of features that allow users to effectively analyze social media content. It provides the ability to scrape data from various platforms such as Telegram and Gab and allows users to gather information, track trends and understand the narratives prevalent in these areas. The toolkit includes advanced algorithms for sentiment analysis, keyword extraction and network mapping.
Journalists can use SMAT to uncover stories, analyze public opinion and identify influential voices in the digital world. Researchers benefit from the ability to conduct extensive analysis of social media data, which contributes to a better understanding of social trends and behaviors. The downside is that journalists don’t always use the app, do they?
Ethical Considerations:
The use of SMAT raises ethical questions related to privacy, consent, and the potential for misuse. While the toolkit is designed to serve the interests of marginalized communities, concerns may arise regarding the collection of sensitive information and the potential impact on individual privacy.
SMAT as an institution has been using their own platform to collect data about political and economical changes in the world. In their article: Fringe reaction to Musk acquiring Twitter
the application categorizes Elon Musk’s supporters as:
The categorization of individuals based on the content they engage with poses a significant concern, particularly when algorithms are employed to distinguish between good and bad political opinions. While the intention behind implementing such algorithms may be rooted in the desire to understand user preferences, it carries the inherent risk of perpetuating biases and misrepresenting individuals’ beliefs.
If these algorithms are not carefully designed and constantly monitored, they can unintentionally reinforce pre-existing stereotypes and contribute to the formation of echo chambers.
The categorization of opinions as right or wrong is subjective and influenced by various factors, including cultural, political and social contexts. Algorithms that categorize users based on their preferences may not capture the nuances of different perspectives. In addition, the potential for unintended consequences, such as increasing political polarization or unfairly stigmatizing certain viewpoints, raises ethical concerns.
It is important to recognize that people are complex and their beliefs often transcend simple categorizations. Those who rely solely on algorithmic categorizations run the risk of simplifying the diversity of human thought and preventing open dialogue. Content analysis should take a more nuanced and human-centered approach that values the subtleties of individual perspectives rather than reducing them to binary classifications.
When implementing apps, it is important for developers and platform administrators to ensure transparency, accountability and regular checks of their algorithms. It must be ensured that the categorization processes are unbiased, free from political influence and respect users’ privacy. A balance between providing personalized content and protecting against algorithmic misjudgment is key to fostering a digital environment that respects the richness of diverse opinions and encourages constructive discourse. Ultimately, the thoughtful design and ethical use of algorithms can contribute to a more inclusive and open online space.
To summarize, SMAT is a powerful tool that has the potential to significantly influence activism, journalism and research in the digital age. Its capabilities in scraping social media content, including platforms such as Telegram and Gab, make it a valuable resource for understanding online discourse. When using SMAT, it is crucial that applications are governed by ethical considerations to ensure that the tool contributes positively to the interests of marginalized communities while respecting individual privacy and consent.
