# Hashtag Recommendation Methods for Twitter and Sina Weibo: A Review
## 1 Introduction  
Social media platforms have become fast-growing and influential media that enable people to communicate with each other easily, share information and search for exciting topics. The number of social media users was 3.6 billion in 2020, and this number is predicted to increase to 4.41 billion users in 2025 ([[https://www.statista.com/statistics/278414/](https://www.statista.com/statistics/278414/)]([https://www.statista.com/statistics/278414/](https://www.statista.com/statistics/278414/)) (accessed on 10 May 2021)). Twitter ([[https://about.twitter.com/company](https://about.twitter.com/company)]([https://about.twitter.com/company](https://about.twitter.com/company)) (accessed on 10 May 2021)) is a microblogging social media platform that permits users to write and share short messages of 280 characters or less, including hashtags, mentions and URLs. These types of short messages are referred to as \"microblogs\" and \"tweets\" [1; 2; 3; 4; 5; 6; 7]. Founded in 2006, Twitter has quickly become an increasingly popular and powerful tool worldwide. According to the Internet Live Stat ([[http://www.internetlivestats.com/twitter-statistics/](http://www.internetlivestats.com/twitter-statistics/)]([http://www.internetlivestats.com/twitter-statistics/](http://www.internetlivestats.com/twitter-statistics/)) (accessed on 10 May 2021)), 500 million messages on average are posted per day by 330 million active users. In July 2020 ([[https://www.statista.com/statistics/242606/](https://www.statista.com/statistics/242606/)]([https://www.statista.com/statistics/242606/](https://www.statista.com/statistics/242606/)) (accessed on 10 May 2021)), the United States had the largest audience size, with 62.55 million users, followed by Japan with 49.1 million users, and India ranked third with 17 million users. Sina Weibo ([[https://www.statista.com/statistics/795303/china-mau-of-sina-weibo/](https://www.statista.com/statistics/795303/china-mau-of-sina-weibo/)]([https://www.statista.com/statistics/795303/china-mau-of-sina-weibo/](https://www.statista.com/statistics/795303/china-mau-of-sina-weibo/)) (accessed on 10 May 2021)), the Chinese equivalent of Twitter, had around 523 million active users in the same year. With the information overload and increase in technology dependency, social recommendations have become a key research area. Social recommendation systems can be defined as techniques or algorithms that automatically suggest the most relevant and interesting data to social media users. Hashtag recommendation is a branch of the social recommendation systems that proposes contemporary and relevant hashtags to users asthey type tweets [5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23]. Choosing the correct hashtag has several benefits: it enables the user to quickly join a discussion and read tweets written by other users [24]. Using hashtags gives the user a chance for their tweets to be noticed and reach a wider audience [25]. Hashtags also help researchers to analyze users' behaviors or to predict the outbreaks of natural disasters and epidemics [26]; they are also helpful for companies to advertise their products and improve customer services and support through users' complaints and comments [27]. In politics, politicians can communicate with the public and advertise their campaigns [28]. Moreover, people can raise and share their voice nationally and globally [29]. For Twitter and Sina Weibo, recommending hashtags helps to enhance discussion as users are guided to use more accurate and relevant hashtags. Adopting the right hashtags helps Twitter/Sina Weibo to eliminate insignificant and noisy hashtags and reduce information overload. Automatically recommending personalized hashtags to users also helps them save time and effort in searching for relevant hashtags. Recommending hashtags by analyzing tweets and extracting information from the Twitter/Sina Weibo hashtag universe can be a very challenging task. One of the challenges is that these tweets and hashtags are _user-generated_.