Understanding ambiences from consumers helps in inspecting market value of an artifact. Data and voice quality of telecom service are often praised and targeted in social networking platforms. There is a need to analyze these opinions to infer renown of service providers. In this context, data is extracted for major Indian telecom service providers from Twitter and FaceBook. Furthermore, performance metrics of these providers are collected from TRAI portal to compare projected thresholds with customer opinions. These datasets are retrieved in predefined timeframe to ensure that information isn’t biased. Towards exploring a prevalent service provider, an ensemble node ranking approach is designed based on ideologies of SVM and RNN algorithms (SVMRNNRank). This approach is modelled based connectivity in the network. Its effectiveness is demonstrated by calculating certain statistical metrics. Comparative analysis reflects that influential nodes identified from SVMRNNRank have better acceptance amongst social network users and TRAI performance indices.