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

机译:网络文本分析,总结在线对话以促进电信行业的营销情报工作

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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.
机译:市场竞争激烈,给公司施加了压力,要求它们采用一种新的更快的方法来支持其营销情报工作。市场营销情报的需求包括收集和分析数据,以便对市场及其竞争做出可靠的决策。如今,来自在线社交网络服务的大量大规模数据已使从市场上的对话中提取有价值的信息(例如用户意见和情感)成为可能。随着竞争的发展,出现了新的挑战,其中包括更快的数据汇总。汇总内容的常见做法是使用wordcloud或出现单词的加权列表。这种方法缺乏问题中单词之间的意义和上下文关系,因为这些单词与可能构成重要短语的其他单词没有任何联系。借助图形表达,我们提出了一种网络文本分析方法,以总结在线社交网络服务中的大型会话。所提出的方法学捕获了词之间的复杂关系,同时仍然保持了快速的总结。在本文中,我们比较了印度尼西亚的三大电信运营商,分别是Telkomsel,XL和Indosat。收集了在线社交网络服务Twitter中有关这些品牌的对话,构建并分析了有关每个品牌的网络文本。

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