Context: The 3rd generation of cryptocurrencies groups together cryptocurrencies as diverse as they are sulphurous, like Dogecoin or Litecoin. While one qualifies as memecoin, the other is of interest to a different category of investors. In our knowledge, no study has independently assessed crypto community economic impact concerning this comparable cryptocurrencies. Method: Our study has retrospectively studied (from 01/01/2015 to 03/11/2021), using open access data, the association strength (using normalized mutual information) as well as the linear correlation (using Pearson’s correlation) between Twitter social networks markers and cryptocurrency economic markers. In addition, we have computed different models in order to forecast past prices values and then we have assessed their precision. Findings and conclusions: While average Dogecoin transaction value is impacted by tweets, Litecoin transactions number and average Litecoin transaction value impacted tweets. Concerning whales, tweets are impacted by Dogecoin whales but any significant relationship was found between Litecoin whales and tweets. According to our ARIMA(0,0,0) models, we have a past values forecasting error of 0.08% on Litecoin and 0.22% on Dogecoin.Therefore, there are thus the beginnings of a scientific rationale in order to build a trading robot based on these big datas. This paper is only for academic discussion, conclusions need to be confirmed by further research.