相关论文: Implicit Location Sharing Detection in Social Medi…

The increasing popularity of the social networking service, Twitter, has made it more involved in day-to-day communications, strengthening social relationships and information dissemination. Conversations on Twitter are now being explored…

Locations, e.g., countries, states, cities, and point-of-interests, are central to news, emergency events, and people's daily lives. Automatic identification of locations associated with or mentioned in documents has been explored for…

We present a new algorithm for inferring the home location of Twitter users at different granularities, including city, state, time zone or geographic region, using the content of users tweets and their tweeting behavior. Unlike existing…

Twitter is an extremely popular social networking platform. Most Twitter users do not disclose their locations due to privacy concerns. Although inferring the location of an individual Twitter user has been extensively studied, it is still…

Twitter has been heavily used as an important channel for communicating and discussing about events in real-time. In such major events, many uninformative tweets are also published rapidly by many users, making it hard to follow the events.…

Information diffusion on social media platforms is often assumed to occur primarily through explicit social connections, such as follower or friend ties. However, information frequently propagates beyond these observable ties -- through…

Users' locations are important for many applications such as personalized search and localized content delivery. In this paper, we study the problem of profiling Twitter users' locations with their following network and tweets. We propose a…

Geographically annotated social media is extremely valuable for modern information retrieval. However, when researchers can only access publicly-visible data, one quickly finds that social media users rarely publish location information. In…

Social media generates an enormous amount of data on a daily basis but it is very challenging to effectively utilize the data without annotating or labeling it according to the target application. We investigate the problem of localized…

The tremendous popularity gained by Online Social Networks (OSNs) raises natural concerns about user privacy in social media platforms. Though users in OSNs can tune their privacy by deliberately deciding what to share, the interaction with…

User's home locations are used by numerous social media applications, such as social media analysis. However, since the user's home location is not generally open to the public, many researchers have been attempting to develop a more…

The impact of social media and its growing association with the sharing of ideas and propagation of messages remains vital in everyday communication. Twitter is one effective platform for the dissemination of news and stories about recent…

In recent years, with the prevalence of social media and smart devices, people causally reveal their locations such as shops, hotels, and restaurants in their tweets. Recognizing and linking such fine-grained location mentions to…

In contrast to much previous work that has focused on location classification of tweets restricted to a specific country, here we undertake the task in a broader context by classifying global tweets at the country level, which is so far…

Research on automatically geolocating social media users has conventionally been based on the text content of posts from a given user or the social network of the user, with very little crossover between the two, and no bench-marking of the…

The geolocation of online information is an essential component in any geospatial application. While most of the previous work on geolocation has focused on Twitter, in this paper we quantify and compare the performance of text-based…

In recent decades, the emergence of social networks has enabled internet service providers (e.g., Facebook, Twitter and Uber) to achieve great commercial success. Link prediction is recognized as a common practice to build the topology of…

In the widely used message platform Twitter, about 2% of the tweets contains the geographical location through exact GPS coordinates (latitude and longitude). Knowing the location of a tweet is useful for many data analytics questions. This…

Nearly all previous work on geo-locating latent states and activities from social media confounds general discussions about activities, self-reports of users participating in those activities at times in the past or future, and self-reports…

The increasing use of social networks generates enormous amounts of data that can be used for many types of analysis. Some of these data have temporal and geographical information, which can be used for comprehensive examination. In this…