The COVID-19 pandemic, declared by the World Health Organization in 2020, not only brought about a global health crisis but also unleashed a flood of information and misinformation on social media platforms. This study delves into the profound effects of the pandemic on mothers and children by employing sentiment analysis on social media data. Analyzing over 30,000 posts from platforms, namely Twitter and Reddit, this research discerns the emotional undercurrents amidst the pandemic chaos. We have used sentiment analysis to classify posts into positive and negative. Further, we have analyzed the classified posts using different sets of machine and deep learning classifiers. To display and examine the current public discourse of worry about the effects of COVID-19 on mothers and children, social media posts are modeled on different topics. Our findings demonstrate that although the participants followed recommendations and safety precautions, their opinions occasionally fluctuated, resulting in a negative impact on society due to misinformation.