Social Media Investigations with A.I. - Video
- Druti Panchal
- Feb 27
- 3 min read
Social media is becoming a key tool for understanding public opinions and predicting situations that need quick action. With approximately 63.7% of the global population actively engaged on social media, a massive amount of data is generated daily.
What if AI could help us understand content on social media better, and provide useful insights for investigations?
Inteliate is a tactical fusion platform designed to ingest both structured and unstructured data, including posts from social media platforms, for intelligence investigations. After ingestion of data, the system is capable of identifying key themes, topics, hashtags and sentiments in posts while also predicting future trends by analysing historical patterns.
How does It Work in Inteliate: Example Use Case
300 user details were collected from Twitter, filtering a specific location, date and time. The dataset included the following user’s information including:
User ID
Name
Screen Name
Create Date
Tweets
Views
Links
Comments
Retweet
Friend Followers
Friend Following
Location
This information is often stored in file formats, such as Excel or CSV. Using Inteliate, we ingested this data file into the system for intelligence investigation purposes. The output generated is as follows.
1. Sentiment Analysis
The system performs contextual sentiment analysis by understanding the overall meaning of articles and posts, keywords, or simple semantics. In this case, most of the tweets were related to two key topics:
Religion: keywords used multiple times- Jesus, Holy, Pray, Christian, Bible.
Technology: keywords used multiple times- AI, OpenAI, Generative, and Science.
2. Historical data analysis:
The system has a capability to analyse patterns in historical data and understand user’s social media behaviours. After analysing the patterns in the dataset, system suggested that the user’s were interested in two themes/topics—one focusing on religion and the other on technological advancements. Hence, it concluded that users likely has diverse interests, regularly discussing both religious beliefs and advancements in technology without any connection between them.
3. Predicting emerging trend:
The system is capable of analysing historical data to identify future trends in social media posts. Based on the uploaded dataset, it predicted that upcoming tweets may frequently include religious keywords like "God," "Lord," "Jesus," "Spirituality," and "Cross." Additionally, terms related to technology, particularly artificial intelligence and chatbots, such as "AI" and "ChatGPT," are also expected to appear more often. This prediction is based on a noticeable upward trend in the use of similar keywords over time, indicating a growing interest of user in both religion and technology.
4. Decision Support System:
Inteliate enabled decision support system, providing options for implementing countermeasures or corrective actions based on media feedback. During this analysis, the system flagged a specific user who consistently posted hate speech and anti-religious content. As a result, an alert was generated for further investigation of this individual, showcasing the system’s ability to offer clear and actionable decision support.
5. Language Analysis:
The system is equipped to analyse posts in multiple languages. In this case, the datasets included posts in Hindi, Arabic, and English. Despite the diversity of languages, the system understood the content, identified key themes, and uncovered hidden patterns, enabling a behavioural analysis of users.
6. Summary Generation:
The system is capable of generating a concise summary of the social media dataset, providing critical insights and key information in a clear and organised manner.
Using such data, Inteliate can analyse individual sentiments and forecast future trends, keeping users informed, vigilant, and aware of emerging developments. Thus, it enables faster and more informed decision-making process.