Big social data and political sentiment: the tweet stream during the UK General Election 2015 campaign

The General Election for the 56th United Kingdom Parliament was held on 7 May 2015. Tweets related to UK politics, not only those with the specific hashtag ”#GE2015”, have been collected in the period between March 1 and May 31, 2015. The resulting dataset contains over 28 million tweets for a total of 118 GB in uncompressed format or 15 GB in compressed format. This study describes the method that was used to collect the tweets and presents some analysis, including a political sentiment index, and outlines interesting research directions on Big Social Data based on Twitter microblogging.

Study on indoor thermal environment and air quality of office rooms controlled by personal displacement ventilation using CFD

Three-dimensional computational simulations are performed to examine indoor environment and micro-environment around human bodies in an office in terms of thermal environment and air quality. In this study, personal displacement ventilation (PDV), including two cases with all seats taken and two middle seats taken, is compared with overall displacement ventilation (ODV) of all seats taken under the condition that supply temperature is 24℃ and air change rate is 60 l/s per workstation. When using PDV, temperature stratification, the characteristic of displacement ventilation, is obviously observed at the position of occupant’s head and clearer in the case with all seats taken. Verticalertical ertical temperature temperature temperature temperature temperature differences below height of the head areare under under under 2℃ in two cases in two cases in two cases in two cases in two cases in two cases in two cases in two cases with all seats taken，and the temperature with PDV is higher than that with ODV. Verticalertical ertical temperature temperature temperature temperature temperature temperature difference is under 3 under 3under 3 under 3℃ in the case in the case in the case in the case in the case in the case in the case with two middle seats taken. CO2 concentration is lower th is lower th is lower this lower this lower than 2 g/man 2 g/m an 2 g/man 2 g/man 2 g/man 2 g/m 3 in the breath zone. in the breath zone. in the breath zone. in the breath zone. in the breath zone. in the breath zone. in the breath zone. in the breath zone. in the breath zone. The results indicate that PDV can be used in the room with big change of occupants’ number to satisfy the need of thermal comfort and air quality. When not all seats are taken, designers should increase supply air requirement or reduce its temperature for thermal comfort. INDEX TERMS

TRCM: a methodology for temporal analysis of evolving concepts in Twitter

The Twitter network has been labelled the most commonly used microblogging application around today. With about 500 million estimated registered users as of June, 2012, Twitter has become a credible medium of sentiment/opinion expression. It is also a notable medium for information dissemination; including breaking news on diverse issues since it was launched in 2007. Many organisations, individuals and even government bodies follow activities on the network in order to obtain knowledge on how their audience reacts to tweets that affect them. We can use postings on Twitter (known as tweets) to analyse patterns associated with events by detecting the dynamics of the tweets. A common way of labelling a tweet is by including a number of hashtags that describe its contents. Association Rule Mining can find the likelihood of co-occurrence of hashtags. In this paper, we propose the use of temporal Association Rule Mining to detect rule dynamics, and consequently dynamics of tweets. We coined our methodology Transaction-based Rule Change Mining (TRCM). A number of patterns are identifiable in these rule dynamics including, new rules, emerging rules, unexpected rules and ?dead' rules. Also the linkage between the different types of rule dynamics is investigated experimentally in this paper.

Conversations on Twitter: structure, pace, balance

Twitter is both a micro-blogging service and a platform for public conversation. Direct conversation is facilitated in Twitter through the use of @’s (mentions) and replies. While the conversational element of Twitter is of particular interest to the marketing sector, relatively few data-mining studies have focused on this area. We analyse conversations associated with reciprocated mentions that take place in a data-set consisting of approximately 4 million tweets collected over a period of 28 days that contain at least one mention. We ignore tweet content and instead use the mention network structure and its dynamical properties to identify and characterise Twitter conversations between pairs of users and within larger groups. We consider conversational balance, meaning the fraction of content contributed by each party. The goal of this work is to draw out some of the mechanisms driving conversation in Twitter, with the potential aim of developing conversational models.

Gender diversity and board performance: women's experiences and perspectives

Despite considerable progress that organizations have made during the past 20 years to increase the representation of women at board level, they still hold few board seats. Drawing on a qualitative study involving 30 companies with women directors in the United Kingdom, the United States, and Ghana, we investigate how the relationship between gender in the boardroom and corporate governance operates. The fi ndings indicate that the presence of a minority of women on the board has an insignifi cant effect on board performance. Yet the chairperson’s role is vital in leading the change for recruiting and evaluating candidates and their commitment to the board with diversity and governance in mind. Our study also sheds light on the multifaceted reasons why women directors appear to be resisting the discourse of gender quotas.