Maggie And Jiggs

Every daily and weekly newspaper has a section devoted to comic strip operas. Some people are extremely attached to certain comic strip characters ..They refuse to buy a newspaper which omits a blow by blow description of the daily lives of their particular favorites. Of all the famous comic strip characters now living on inside pages of our great newspapers, two of the best-known and best-loved are Jiggs and his nagging, fault-finding wife, Maggie

Revisiting revisitation in computer interaction: organic bookmark management.

According to Milic-Frayling et al. (2004), there are two general ways of user browsing i.e. search (finding a website where the user has never visited before) and revisitation (returning to a website where the user has visited in the past). The issue of search is relevant to search engine technology, whilst revisitation concerns web usage and browser history mechanisms. The support for revisitation is normally through a set of functional built-in icons e.g. History, Back, Forward and Bookmarks. Nevertheless, for returning web users, they normally find it is easier and faster to re-launch an online search again, rather than spending time to find a particular web site from their personal bookmark and history records. Tauscher and Greenberg (1997) showed that revisiting web pages forms up to 58% of the recurrence rate of web browsing. Cockburn and McKenzie (2001) also stated that 81% of web pages have been previously visited by the user. According to Obendorf et al. (2007), revisitation can be divided into four classifications based on time: short-term (72.6% revisits within an hour), medium-term (12% revisits within a day and 7.8% revisits within a week), and long-term (7.6% revisits longer than a week)

How Constraints Affect Content: The Case of Twitter's Switch from 140 to 280 Characters

It is often said that constraints affect creative production, both in terms of form and quality. Online social media platforms frequently impose constraints on the content that users can produce, limiting the range of possible contributions. Do these restrictions tend to push creators towards producing more or less successful content? How do creators adapt their contributions to fit the limits imposed by social media platforms? To answer these questions, we conduct an observational study of a recent event: on November 7, 2017, Twitter changed the maximum allowable length of a tweet from 140 to 280 characters, thereby significantly altering its signature constraint. In the first study of this switch, we compare tweets with nearly or exactly 140 characters before the change to tweets of the same length posted after the change. This setup enables us to characterize how users alter their tweets to fit the constraint and how this affects their tweets' success. We find that in response to a length constraint, users write more tersely, use more abbreviations and contracted forms, and use fewer definite articles. Also, although in general tweet success increases with length, we find initial evidence that tweets made to fit the 140-character constraint tend to be more successful than similar-length tweets written when the constraint was removed, suggesting that the length constraint improved tweet quality.Comment: To appear in the Proceedings of AAAI ICWSM 201

An integer programming clustering approach with application to recommendation systems

Recommendation systems have become an important research area. Early recommendation systems were based on collaborative filtering, which uses the principle that if two people enjoy the same product they are likely to have common favorites. We present an alternative recommendation approach based on finding clusters of similar customers using integer programming model which is to find the minimal number of clusters subjected to several similarity measures. The proposed recommendation method is compared with collaborative filtering, and the experimental results show that it provides relatively high prediction accuracy as well as relatively small variance

Sabotage in Asymmetric Contests – An Experimental Analysis

In a contest players compete for winning a prize by effort and thereby increasing their probability of winning. Contestants, however, could also improve their own relative position by harming the other players. We experimentally analyze contests with heterogeneous agents who may individually sabotage each other. Our results suggest that sabotaging behavior systematically varies with the composition of different types of agents in a contest. Moreover, if the saboteur's identity is revealed sabotage decreases while retaliation motives prevail.Contest, Experiments, Sabotage, Tournament