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Linguistically Motivated SemanticAggregation Engines

Co-funded by the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement no 288024.

urrently, daily monitoring of social networking sites, e.g. analysis of tweets, is mostlydone manually. However, the spectacular growth of user generated content makes itine�cient, causing a high demand for tools capable of automatically detecting reputa-tion alerts. Unfortunately, online reputation management (ORM) applications available onmarket still cannot provide professionals with satisfactory solutions.

Some of the research questions related to information access over social media (and amongthem, those related to ORM) are addressed by the European Union project LiMoSINe,Linguistically Motivated Semantic Aggregation Engines, formed by a consortium of fouruniversities (University of Amsterdam, University of Glasgow, University of Trento, and Universidad Nacional de Educación a Distancia) and two companies: Fundacio Barcelona Media Universitat Pompeu Fabra and a communication consultancy �rm, LLORENTE & CUENCA.

The main objectives of this project are:

• LiMoSINe integrates the research activities of leading researchers across diverse topics with a view to enabling new kinds of language-based search technology.

• LiMoSINe´s vision is to allow access to online information from a documentcentric search paradigm focused on returning disconnected atomic pieces that understands the user´s questions and intent.

• LiMoSINe´s aggregation engines automatically organize search results in intelligent and meaningful ways . The objective is to build search and recommendation systems that will understand a user´s intent, discover and organize facts, identify opinions, experiences and trends, all from multilingual online sources and open online sources and open online databases, like Twitter, YouTube, MusicBrainz, Flickr, Wikipedia, etc.

LiMoSiNe Project

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urrently, daily monitoring of social networking sites, e.g. analysis of tweets, is mostlydone manually. However, the spectacular growth of user generated content makes itine�cient, causing a high demand for tools capable of automatically detecting reputa-tion alerts. Unfortunately, online reputation management (ORM) applications available onmarket still cannot provide professionals with satisfactory solutions.

Some of the research questions related to information access over social media (and amongthem, those related to ORM) are addressed by the European Union project LiMoSINe,Linguistically Motivated Semantic Aggregation Engines, formed by a consortium of fouruniversities (University of Amsterdam, University of Glasgow, University of Trento, and Universidad Nacional de Educación a Distancia) and two companies: Fundacio Barcelona Media Universitat Pompeu Fabra and a communication consultancy �rm, LLORENTE & CUENCA.

The main objectives of this project are:

• LiMoSINe integrates the research activities of leading researchers across diverse topics with a view to enabling new kinds of language-based search technology.

• LiMoSINe´s vision is to allow access to online information from a documentcentric search paradigm focused on returning disconnected atomic pieces that understands the user´s questions and intent.

• LiMoSINe´s aggregation engines automatically organize search results in intelligent and meaningful ways . The objective is to build search and recommendation systems that will understand a user´s intent, discover and organize facts, identify opinions, experiences and trends, all from multilingual online sources and open online sources and open online databases, like Twitter, YouTube, MusicBrainz, Flickr, Wikipedia, etc.

The LiMoSINe Project is now developing 5 demonstrators: ORMA, ThemeStreams, Flickr Demo, DEESSE and Streamwatchr.

ORMA

ORMA (Online Reputation Monitoring Assistant) is an interactive annotation tool.

It helps online reputation experts to label tweets related to a client with information essential for the analysis of the client’s reputation.

The current version of the assistant works with tweets in English and Spanish. Besides storing and organising manually introduced data, it can also prompt automatically generated labels which can be validated or corrected by analysts. The main goal is to facilitate the daily work of online reputation experts and increase their e�ciency.

ThemeStreams

ThemeStreams is a demonstrator aimed at giving insight into who started a topic in social media. It monitors tweets from four groups of people, namely, politicians, political journalists, lobbyists, and other in�uencers and visualizes the dynamics of a given topic and the discussion around it.

It indexes and visualises tweets as streams of in�uences, and shows this as a streamgraph of the political landscape over time. This shows when somebody said something, and how many people found that interesting.

ThemeStreams can be adapted to other typed data outside of the political landscape. It is useful to media analysts for better understanding who said what, and how the discussion around a topic has evolved among groups of people and over time. Check it out at http://themestreams.xtas.net

Demonstrators

ThemeStreams: visualizing the Stream of themes discussed In Politics

Who started talking about this issue?

urrently, daily monitoring of social networking sites, e.g. analysis of tweets, is mostlydone manually. However, the spectacular growth of user generated content makes itine�cient, causing a high demand for tools capable of automatically detecting reputa-tion alerts. Unfortunately, online reputation management (ORM) applications available onmarket still cannot provide professionals with satisfactory solutions.

Some of the research questions related to information access over social media (and amongthem, those related to ORM) are addressed by the European Union project LiMoSINe,Linguistically Motivated Semantic Aggregation Engines, formed by a consortium of fouruniversities (University of Amsterdam, University of Glasgow, University of Trento, and Universidad Nacional de Educación a Distancia) and two companies: Fundacio Barcelona Media Universitat Pompeu Fabra and a communication consultancy �rm, LLORENTE & CUENCA.

The main objectives of this project are:

• LiMoSINe integrates the research activities of leading researchers across diverse topics with a view to enabling new kinds of language-based search technology.

• LiMoSINe´s vision is to allow access to online information from a documentcentric search paradigm focused on returning disconnected atomic pieces that understands the user´s questions and intent.

• LiMoSINe´s aggregation engines automatically organize search results in intelligent and meaningful ways . The objective is to build search and recommendation systems that will understand a user´s intent, discover and organize facts, identify opinions, experiences and trends, all from multilingual online sources and open online sources and open online databases, like Twitter, YouTube, MusicBrainz, Flickr, Wikipedia, etc.

Flickr Demo

The Flickr Demo allows the user to annotate images related to a large scale social event. On selec-tion of an image, the user is o�ered automatic tag recommendations (based on existing tags added by the user), as well as related tweets and Wikipedia content.

We achieve this by o�ering the user a number of photo tagging methods:

• Manual Tagging • Tag Recommendations • Related Tweets: tweets tagged with the hash related to the event • Related Wikipedia content

The entity-Driven Exploratory and sErendipitous Search SystEm (DEESE) enables a serendipitous exploration of complex data extracted from Yahoo Answers, by providing a high-level overview of the information in the form of an enriched entity network.

Our demo support a serendipitous and exploratory search over Yahoo Answers, giving user an unprecedented capability of exploring the wealth of data enclosed in it by many di�erent pers-pectives. Furthermore, it allows to exploit the advantages of the freedom of conversation on Yahoo Answers, which contains within it opinions, rumors, and social interest and approval.

Streamwatchr is a demonstrator aimed at understan- ding the world, as it happens. Streamwatchr moni- tors, interprets and analyzes social media for speci�c user activities, e.g, listening to music, watching a movie, eating, and visualizes these interpretations in real-time. The interpretation happens via mapping the text in social media to vertical and horizontal knowledge bases (e.g., Musicbrainz and Wikipedia).

Currently, Streamwatchr focuses on music-related tweets, and o�ers a new and playful way to engage with music. Besides monitoring the latest popular trends and provide recommendations for interesting new music discoveries, Streamwatchr monitors what people sing along and o�ers statistics on the most sung-alongparts of each song.

Streamwatchr is great for both discovering new music and checking charts, and tracking artist song trends. Check it out at http://streamwatchr.com

Streamwatchr

DEESSE

urrently, daily monitoring of social networking sites, e.g. analysis of tweets, is mostlydone manually. However, the spectacular growth of user generated content makes itine�cient, causing a high demand for tools capable of automatically detecting reputa-tion alerts. Unfortunately, online reputation management (ORM) applications available onmarket still cannot provide professionals with satisfactory solutions.

Some of the research questions related to information access over social media (and amongthem, those related to ORM) are addressed by the European Union project LiMoSINe,Linguistically Motivated Semantic Aggregation Engines, formed by a consortium of fouruniversities (University of Amsterdam, University of Glasgow, University of Trento, and Universidad Nacional de Educación a Distancia) and two companies: Fundacio Barcelona Media Universitat Pompeu Fabra and a communication consultancy �rm, LLORENTE & CUENCA.

The main objectives of this project are:

• LiMoSINe integrates the research activities of leading researchers across diverse topics with a view to enabling new kinds of language-based search technology.

• LiMoSINe´s vision is to allow access to online information from a documentcentric search paradigm focused on returning disconnected atomic pieces that understands the user´s questions and intent.

• LiMoSINe´s aggregation engines automatically organize search results in intelligent and meaningful ways . The objective is to build search and recommendation systems that will understand a user´s intent, discover and organize facts, identify opinions, experiences and trends, all from multilingual online sources and open online sources and open online databases, like Twitter, YouTube, MusicBrainz, Flickr, Wikipedia, etc.

LiMoSINe has promoted RepLab, a benchmarking activity in the area of Online Reputation Management (ORM).

It is a competitive evaluation exercise for ORM systems orga-nised by UNED, UvA, and LLORENTE & CUENCA that aims at:

• Defining relevant challenges and specifying appropriate resources for automatic ORM • Building test collections for benchmarking purposes

• Comparing state-of-art systems and algorithms

Created in 2012 as an activity of Cross Language Evaluation Forum (CLEF), RepLab has covered such tasks as �ltering, reputation polarity classi�cation, grouping and ranking of entity related tweets.

RepLab 2014 will focus on Reputation Monitoring in Twitter, targeting two new tasks: categorization of messages with respect to standard reputation dimensions and classi�ca-tion of Twitter pro�les (author pro�ling). The results will be discussed at the CLEF 2014 Conference in She�eld (UK), 15-18 September 2014.

RepLab

urrently, daily monitoring of social networking sites, e.g. analysis of tweets, is mostlydone manually. However, the spectacular growth of user generated content makes itine�cient, causing a high demand for tools capable of automatically detecting reputa-tion alerts. Unfortunately, online reputation management (ORM) applications available onmarket still cannot provide professionals with satisfactory solutions.

Some of the research questions related to information access over social media (and amongthem, those related to ORM) are addressed by the European Union project LiMoSINe,Linguistically Motivated Semantic Aggregation Engines, formed by a consortium of fouruniversities (University of Amsterdam, University of Glasgow, University of Trento, and Universidad Nacional de Educación a Distancia) and two companies: Fundacio Barcelona Media Universitat Pompeu Fabra and a communication consultancy �rm, LLORENTE & CUENCA.

The main objectives of this project are:

• LiMoSINe integrates the research activities of leading researchers across diverse topics with a view to enabling new kinds of language-based search technology.

• LiMoSINe´s vision is to allow access to online information from a documentcentric search paradigm focused on returning disconnected atomic pieces that understands the user´s questions and intent.

• LiMoSINe´s aggregation engines automatically organize search results in intelligent and meaningful ways . The objective is to build search and recommendation systems that will understand a user´s intent, discover and organize facts, identify opinions, experiences and trends, all from multilingual online sources and open online sources and open online databases, like Twitter, YouTube, MusicBrainz, Flickr, Wikipedia, etc.

Linguistically Motivated SemanticAggregation Engines

More Information

LLORENTE & CUENCA

Members of the consortium LiMoSINe Project

If you have any further questions or you want to interview one of the team leaders, please do not hesitate to contact Vanessa Álvarez or Ana Pitart in these emails:

valvarez@llorenteycuenca.comapitart@llorenteycuenca.com

Universiteit van Amsterdam, The NetherlandsMaarten de Rijke (Scienti�c Coordination and professor of Information Processing and Internet, University of Amsterdam)

Manos Tsagkias (Postdoctoral researcher in Information Retrieval and Predictive Analytics , University of Amsterdam)

University of Glasgow, United KingdomJoemon M Jose (Professor at the Department of Computing Science, University of Glasgow)

Fundacio Barcelona Media Universitat Pompeu Fabra, SpainMounia Lalmas (Visiting Principal Scientist, Yahoo! Research Barcelona)

Universita degli studi di Trento, Italy Alessandro Moschitti (Assistant Professor at the Information Engineering and Computer Science Department, University of Trento) Llorente & Cuenca Madrid SL, SpainAdolfo Corujo (Partner and Iberian General Manager, LLORENTE & CUENCA)

Universidad Nacional de Educación a Distancia, SpainJulio Gonzalo (Assistant Professor and Member of the UNED group in Natural Language Processing and Information Retrieval)

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