Network text analysis to summarize online conversations for marketing intelligence efforts in telecommunication industry

Market tight competition put pressure the companies to employ a new and faster way to support their marketing intelligence effort. The need of marketing intelligence includes gathering and analyzing data for confident decision making about market and its competition. Today, the abundant large scale data from online social network services has made possible to extract valuable information such as user opinions and sentiment from the conversations in the market. As the competition arise, new challenge emerged, which include faster data summarization. The common practice of summarize contents is using wordcloud or weighted list of appearance words. This approach is lack of sense and contextual relations between words in questions, because the words has no connection with other words that might construct an important phrase. With the help of graph formulation, we propose a methodology of network text analysis to summarize large conversation in online social network services. This proposed methodology capture complex relations between words, while still maintain fast summarization. In this paper, we compare three major telecommunication provider in Indonesia, which is Telkomsel, XL and Indosat. The conversations about those brands in online social network services Twitter is collected, Network text about each brands are constructed and analyzed.