activity
20092018
most citedTwitter mood predicts the stock market

5.2k citations · 6k across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2018★ 80 cited

A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements

Yingjie Hu, Huina Mao, Grant McKenzie

Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relat…

q-fin.ST2011★ 41 cited

Predicting Financial Markets: Comparing Survey, News, Twitter and Search Engine Data

Huina Mao, Scott Counts, Johan Bollen

Financial market prediction on the basis of online sentiment tracking has drawn a lot of attention recently. However, most results in this emerging domain rely on a unique, particu…

cs.SI2011★ 268 cited

Happiness is assortative in online social networks

Johan Bollen, Bruno Goncalves, Guangchen Ruan +1

Social networks tend to disproportionally favor connections between individuals with either similar or dissimilar characteristics. This propensity, referred to as assortative mixin…

cs.CE2010★ 5.2k cited

Twitter mood predicts the stock market

Johan Bollen, Huina Mao, Xiao-Jun Zeng

Behavioral economics tells us that emotions can profoundly affect individual behavior and decision-making. Does this also apply to societies at large, i.e., can societies experienc…

cs.CY2009★ 319 cited

Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena

Johan Bollen, Alberto Pepe, Huina Mao

Microblogging is a form of online communication by which users broadcast brief text updates, also known as tweets, to the public or a selected circle of contacts. A variegated mosa…