text: In previous work we reported that resources linked in tweets disappeared at the rate of 11 in the first year followed by 7.3 each year afterwards. We also found that in the first year 6.7 , and 14.6 in each subsequent year, of the resources were archived in public web archives. In this paper we revisit the same dataset of tweets and find that our prior model still holds and the calculated error for estimating percentages missing was about 4 , but we found the rate of archiving produced a higher error of about 11.5 . We also discovered that resources have disappeared from the archives themselves (7.89 ) as well as reappeared on the live web after being declared missing (6.54 ). We have also tested the availability of the tweets themselves and found that 10.34 have disappeared from the live web. To mitigate the loss of resources on the live web, we propose the use of a "tweet signature". Using the Topsy API, we extract the top five most frequent terms from the union of all tweets about a resource, and use these five terms as a query to Google. We found that using tweet signatures results in discovering replacement resources with 70+ textual similarity to the missing resource 41 of the time.
  @cite_1: 
  @cite_19: Personal weblogs (blogs), provide individuals with the opportunity to write freely and express themselves online in the presence of others. In such situations, what do bloggers write about, and what are their motivations for blogging? Using a large blog corpus annotated with the LIWC text analysis program, we examine the content of blogs to provide insight into the role of personality in motivation for blogging. As predicted, we find that highly Neurotic authors use blogs to serve a cathartic or auto-therapeutic function, and reflect mainly upon themselves and negative emotions. Highly Extraverted blog authors, as expected, use blogs to document their lives at a high level, and uniquely interact directly with the reader. Additionally Extraverts use blogs to vent both positive and negative emotions. Bloggers who are high scorers on the Openness trait are more concerned with leisure activities, although they are more evaluative than intellectual, whereas high Conscientiousness bloggers tend to report daily life – and work – around them. As in other contexts, expressing positive rather than negative emotions is associated with high Agreeableness, but that trait is associated with self reference to a greater degree in blogs than elsewhere. In general, findings are consistent with other contexts indicating that bloggers tend to adapt to the possibilities of the medium, rather than try to present themselves differently.
  @cite_16: Micro-blogs, a relatively new phenomenon, provide a new communication channel for people to broadcast information that they likely would not share otherwise using existing channels (e.g., email, phone, IM, or weblogs). Micro-blogging has become popu-lar quite quickly, raising its potential for serving as a new informal communication medium at work, providing a variety of impacts on collaborative work (e.g., enhancing information sharing, building common ground, and sustaining a feeling of connectedness among colleagues). This exploratory research project is aimed at gaining an in-depth understanding of how and why people use Twitter - a popular micro-blogging tool - and exploring micro-blog's poten-tial impacts on informal communication at work.
  @cite_13: Understanding how users behave when they connect to social networking sites creates opportunities for better interface design, richer studies of social interactions, and improved design of content distribution systems. In this paper, we present a first of a kind analysis of user workloads in online social networks. Our study is based on detailed clickstream data, collected over a 12-day period, summarizing HTTP sessions of 37,024 users who accessed four popular social networks: Orkut, MySpace, Hi5, and LinkedIn. The data were collected from a social network aggregator website in Brazil, which enables users to connect to multiple social networks with a single authentication. Our analysis of the clickstream data reveals key features of the social network workloads, such as how frequently people connect to social networks and for how long, as well as the types and sequences of activities that users conduct on these sites. Additionally, we crawled the social network topology of Orkut, so that we could analyze user interaction data in light of the social graph. Our data analysis suggests insights into how users interact with friends in Orkut, such as how frequently users visit their friends' or non-immediate friends' pages. In summary, our analysis demonstrates the power of using clickstream data in identifying patterns in social network workloads and social interactions. Our analysis shows that browsing, which cannot be inferred from crawling publicly available data, accounts for 92 of all user activities. Consequently, compared to using only crawled data, considering silent interactions like browsing friends' pages increases the measured level of interaction among users.
summary: Along with understanding the nature of the social media, researchers analyzed user behavior on the social networks in general. By analyzing user activity click logs, aimed to get a better understanding of social interactions social browsing patterns @cite_13 . Zhao and Rosson aimed to explore the reasons of how and why people use Twitter and this use's impact on informal communication at work @cite_16 . Following the how and the why, attempted to answer the next question of what is the user-generated content is about by investigating personal weblogs to detect the effects of personality, topic type, and the general motivation in published blogs @cite_19 . Yang and Counts investigated the information diffusion speed, scale and range in Twitter and how they could be predicted @cite_1 .