为了能够实时、高效地获取Twitter数据,在分析了传统采集方法的缺陷后,提出了基于Twitter List API和Lookup API的用户数据采集方案。该方案通过对用户进行分类,进而精确控制API的调用频率。经在超过26万Twitter用户和600万条消息的一...为了能够实时、高效地获取Twitter数据,在分析了传统采集方法的缺陷后,提出了基于Twitter List API和Lookup API的用户数据采集方案。该方案通过对用户进行分类,进而精确控制API的调用频率。经在超过26万Twitter用户和600万条消息的一系列实验证明,通过两套方案的结合可以实现Twitter用户数据高效实时的获取。展开更多
Thanksgiving and Christmas are two major holidays in the United States. Many people use social media to stay connected with their families and friends, including sharing their holiday experiences. This study utilized ...Thanksgiving and Christmas are two major holidays in the United States. Many people use social media to stay connected with their families and friends, including sharing their holiday experiences. This study utilized a stream of millions of tweets on Twitter to explore how people feel about these two holidays through real-time sentiment analysis. With help of Twitter Streaming API, we discovered the patterns of sentiment changes by hour before and after the two holidays in 2011, thus providing a unique peek into the celebration of these holidays that could not be accomplished with traditional methods. Our analysis suggested that in 2011 people had higher sentiment toward Christmas than Thanksgiving on average. The sentiment reached its maximum on the Thanksgiving Day and on The Christmas Eve and Christmas Day, highlighting stronger zeal for Christmas than Thanksgiving, while remained a stable and lower sentiment before and after the holidays. Typically there was a peak of sentiment toward Thanksgiving and Christmas in the morning of each day around 9:00am (EST). On the Thanksgiving Day the number of tweets on shopping increased rapidly and monotonically to its maximum as time approaching the midnight when people thinking of shopping on the Black Friday, but unexpectedly the sentiment toward shopping dropped quickly and monotonically, displaying the exact opposite trend. We also investigated the shopping distraction on the theme of these two holidays. It was found that there were more people talking about thankfulness than shopping during the Thanksgiving season, but more people talking about shopping than Jesus during the Christmas season.展开更多
Internet takes a role as a place for communication between people beyond a space simply for the acquisition of information.Recently,social network service(SNS)reflecting human’s basic desire for talking and communica...Internet takes a role as a place for communication between people beyond a space simply for the acquisition of information.Recently,social network service(SNS)reflecting human’s basic desire for talking and communicating with others is focused on around the world.And location-based service(LBS)is a service that provides various life conveniences like improving productivity through location information,such as GPS and WiFi.This paper suggests an application combining LBS and SNS based on Android OS.By using smart phone which is personal mobile information equipment,it combines location information with user information and SNS so that the service can be developed.It also maximizes sharing and use of information via twit based on locations of friends.This proposed system is aims for users to show online identity more actively and more conveniently.展开更多
文摘为了能够实时、高效地获取Twitter数据,在分析了传统采集方法的缺陷后,提出了基于Twitter List API和Lookup API的用户数据采集方案。该方案通过对用户进行分类,进而精确控制API的调用频率。经在超过26万Twitter用户和600万条消息的一系列实验证明,通过两套方案的结合可以实现Twitter用户数据高效实时的获取。
文摘Thanksgiving and Christmas are two major holidays in the United States. Many people use social media to stay connected with their families and friends, including sharing their holiday experiences. This study utilized a stream of millions of tweets on Twitter to explore how people feel about these two holidays through real-time sentiment analysis. With help of Twitter Streaming API, we discovered the patterns of sentiment changes by hour before and after the two holidays in 2011, thus providing a unique peek into the celebration of these holidays that could not be accomplished with traditional methods. Our analysis suggested that in 2011 people had higher sentiment toward Christmas than Thanksgiving on average. The sentiment reached its maximum on the Thanksgiving Day and on The Christmas Eve and Christmas Day, highlighting stronger zeal for Christmas than Thanksgiving, while remained a stable and lower sentiment before and after the holidays. Typically there was a peak of sentiment toward Thanksgiving and Christmas in the morning of each day around 9:00am (EST). On the Thanksgiving Day the number of tweets on shopping increased rapidly and monotonically to its maximum as time approaching the midnight when people thinking of shopping on the Black Friday, but unexpectedly the sentiment toward shopping dropped quickly and monotonically, displaying the exact opposite trend. We also investigated the shopping distraction on the theme of these two holidays. It was found that there were more people talking about thankfulness than shopping during the Thanksgiving season, but more people talking about shopping than Jesus during the Christmas season.
基金MKE(the Ministry of Knowledge Economy),Korea,under the ITRC(Infor mation Technology Research Center)support program supervised by the NIPA(National IT Industry Promotion Agency)(NIPA-2011-C1090-1121-0010)
文摘Internet takes a role as a place for communication between people beyond a space simply for the acquisition of information.Recently,social network service(SNS)reflecting human’s basic desire for talking and communicating with others is focused on around the world.And location-based service(LBS)is a service that provides various life conveniences like improving productivity through location information,such as GPS and WiFi.This paper suggests an application combining LBS and SNS based on Android OS.By using smart phone which is personal mobile information equipment,it combines location information with user information and SNS so that the service can be developed.It also maximizes sharing and use of information via twit based on locations of friends.This proposed system is aims for users to show online identity more actively and more conveniently.
