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It is difficult to build our own social data set because data in social media is generally too vast and noisy. The aim of this study is to specify design and implementation details of the Twitter data collecting tool with a rule‐based filtering module. Additionally, the paper aims to see how people communicate with each other through social networks in a case study with rule‐based analysis.

The authors developed a java‐based data gathering tool with a rule‐based filtering module for collecting data from Twitter. This paper introduces the design specifications and explain the implementation details of the Twitter Data Collecting Tool with detailed Unified Modeling Language (UML) diagrams. The Model View Controller (MVC) framework is applied in this system to support various types of user interfaces.

The Twitter Data Collecting Tool is able to gather a huge amount of data from Twitter and filter the data with modest rules for complex logic. This case study shows that a historical event creates buzz on Twitter and people's interests on the event are reflected in their Twitter activity.

Applying data‐mining techniques to the social network data has so much potential. A possible improvement to the Twitter Data Collecting Tool would be an adaptation of a built‐in data‐mining module.

This paper focuses on designing a system handling massive amounts of Twitter Data. This is the first approach to embed a rule engine for filtering and analyzing social data. This paper will be valuable to those who may want to build their own Twitter dataset, apply customized filtering options to get rid of unnecessary, noisy data, and analyze social data to discover new knowledge.

In the past 20 years, Macao has experienced phenomenal economic growth driven by the liberalization of its casino sector. This growth has been enabled by massive influxes of foreign capital and migrant labor that have dramatically altered the city’s ethnic landscape. In this paper, the author examines the demographic changes Macao has experienced as a result of the casino boom, and situates the city’s current economic growth and ethnic diversification within its long history as a multi-ethnic city.

Building on Nancy Foner’s notion of “contexts of settlement,” the study draws on census materials, policy statements, newspaper articles and ethnographic materials to examine how changing ideologies of globalization help shape the categories through which ethnic diversity itself is conceptualized.

The paper has three main findings. First, despite the Macao government’s multicultural rhetoric, its labor and residency policies that prevent migrant workers from settling in Macao may paradoxically serve to maintain the ethnic status quo ante. Second, the new contexts of settlement engendered by Macao’s casino globalization may be amplifying fissures within the ethnic category “Chinese.” And third, discourses of globalization, regulations on immigration, and classificatory systems governing ethnic diversity that were instituted under Portuguese rule have both helped shape these new contexts and been reworked in the process.

As the processes of urbanization, economic integration and transnational migration continue to accelerate throughout East Asia, the goal of creating inclusive, equitable multi-ethnic urban societies will require closer examination of the relationship between particular modes and ideologies of “global” engagement, patterns of and policies toward migration and the concepts and categories through which diversity is measured. This approach to understanding multi-ethnic Macao may serve as an example.