Using the Data365 API to Combat Social Media Manipulation

Combating Social Media Manipulation

Challenge: Manipulative practice of fake accounts, purchased engagements and dark web activities are besieging the social media platforms. These threats put the authenticity of online interactions and decades of trust in technology at risk.

Solution: The public data provided by Data365 Social Media API proved an indispensable means of identifying and grouping manipulative services within the black market. For instance, the Data science company team found a network of services purveying fake likes and followers that charged many different prices. Learn these dynamics and what Data science company built for countermeasures that disrupt these services, and they can help to reinstate authenticity on social media interactions.

Specific findings:

• Price discrepancies It found these networks charged different rates for doing similar manipulations, which could be used by exploiters to disrupt them.
• Dark web links Data365 API data was used by Data science company to trace from connection of surface web manipulation service to more covert dark web activity for better counter strategies.

Large-scale User Profile Analysis

Challenge: Studying hundreds of social media profiles to understand how misinformation spreads and how government rules affect users.

Solution: Data science company studied over 315,000 profiles through the data provided by Data365 APIs, discovering key trends in user demographics and posting behaviors following the restrictions. For instance, users in regions modified by the restrictions showed increased connectivity and a shift toward younger demographics.

Specific findings:

• Demographic shifts Post-ban, the user base in certain regions skewed younger, indicating a change in the platform's user demographics.
• Increased connectivity Users under restriction became more connected, likely as a means of maintaining communication despite the restrictions.

Detection And Mitigation Of Bot Activity

Challenge: Since the type of social network is the one that allows bots to appear differently from real users. The prevalence of bots on social networks complicates the difference between real users and automated accounts, making it easier for misinformation to spread unchecked.

Solution: Data science company was using Data365’s APIs to detect the bot like behavior across all social media platforms. Through pattern analysis with such things as posting frequency and content duplication, Data science company accurately identified bot networks. It enabled them to diminish the effect of these bots since they could cut them out, or defeat them so that their role in propagating misinformation was diminished.

Specific findings:

• Bot networks Data science company identified many large bot networks that spread false information. By knowing what they were doing, they were able to greatly reduce their footprint on the platform.
• Behavioral patterns Specific posting behaviors, including highly frequent posting, and repetitive content were used as indica to detect bots.